Pseudolife Memory
Persistent memory for MCP-compatible agents: memory bank, fact cortex, dreams, graph.
Open source Open in the app JSON README (API)
About
Persistent memory for MCP-compatible agents: memory bank, fact cortex, dreams, graph.
Details
- Kind
- MCP servers
- Topic
- AI, RAG & memory
- Publisher
- pseudogiant-xr
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 0.15.0
- Stars
- 4
- Forks
- 1
- Open pull requests
- 1
- Last push
- 2026-09-04T10:24:14Z
- Repository state
- ativo
- Language
- Python
- License
- Apache-2.0
- Added
- 2026-08-29 03:02:11
- Updated
- 2026-09-03 16:00:56
- Origin id
io.github.Pseudogiant-xr/pseudolife-mcp
README
# Pseudolife-MCP
<!-- mcp-name: io.github.Pseudogiant-xr/pseudolife-mcp -->
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[](LICENSE)
[](https://pypi.org/project/pseudolife-mcp/)
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**Persistent long-term memory for Claude Code, Codex, and other MCP clients.**
An MCP server that gives coding agents a long-term memory that persists across
sessions — surviving context compactions and fresh tasks. Your coding agent is
the intelligence; this server is its memory on disk.
What you get:
- **Associative memory with honest forgetting** — a flat similarity store
ranked by hybrid dense-plus-lexical retrieval, with contradiction
detection and supersession. (The measured verdict: a preregistered
ablation campaign found the previous 8-band continuum tied a flat store
on every gate, so the simpler structure ships; the continuum remains
one config line away.)
- **Canonical facts, not vibes** — one *current* value per `entity.attribute`
slot (or a member set, for slots that hold many concurrent values);
corrections supersede rather than silently overwrite, and the full
version history survives.
- **Dreams** — a bundled local extractor, or any OpenAI-compatible endpoint
(a Claude model on your Max plan, a GPT-5.6 model on a ChatGPT plan, LM
Studio, Ollama, vLLM), consolidates the memory stream into facts and a
knowledge graph while you're not looking.
- **Lessons from its own work** — successes, dead-ends, and your corrections
become do/avoid guidance surfaced at the start of every session.
- **A web console to watch it think** — the Cortex Console above, plus cited
world facts, session episodes, and document RAG.
Measured, with receipts — the **full 500-question LongMemEval sweep**, all
six question types, and every number ships with its committed run artifact:
| LongMemEval oracle, 500 questions | naive RAG | commit-gated cascade |
|---|---:|---:|
| accuracy, all six question types | 0.688 | 0.690 |
| context tokens per question | ~1210 | **~883** |
| knowledge-update slice (78 of the 500) | 0.859 | ~~0.936~~ (retired — see below) |
Equal accuracy to naive RAG across the whole benchmark on **~73% of the
context**, and better calibrated about what it does not know: on BEAM-100K's
abstention questions the fact spine scores **0.950** against naive RAG's
0.775, unchanged under two independent judges. Read that as calibration,
not recall — in the budget-matched five-arm run of 2026-09-02 (rag 0.725 there;
one replicate, local judge) an arm served no memory at all scores 1.000 on
the same questions, because refusing is the right answer there and an
empty context always refuses. The fact spine loses where an answer has to
be aggregated across sessions. Graded by a local, byte-reproducible judge (the cross-judge check
names its second judge) — compare within rows, never against GPT-judged
leaderboards.
> **Retired 2026-08-25 (#188): the 0.936 knowledge-update headline.** It was
> measured on the 2026-07-30 bench stack (Qwen3.6-27B answerer and judge).
> Re-running the same 78 questions after the 2026-08-17 migration to
> Qwen3.8-27B puts the cascade at **0.846**, below the naive-RAG control —
> which lands on 0.859 on both stacks. The cascade serves the fact-spine
> answer unless that channel says "I don't know", so it measures the
> *answerer's* abstention behaviour as much as the memory: 32/78 abstentions
> at 46/46 commit precision on the old stack, 22/78 at 0.839 on the new one.
> The 500-question table above is on the older judge and has not been
> re-judged, so read its cascade row as an upper bound.
Full tables, the per-type breakdown, both stacks side by side, and every
artifact: [Benchmarks](docs/guide/benchmarks.md).
## Quickstart
Two commands. No Docker, no database to set up, no container runtime:
```bash
pip install "pseudolife-mcp[lite]"
claude mcp add --scope user pseudolife-memory -- pseudolife-mcp
```
Codex instead of Claude Code — same shape:
```bash
pip install "pseudolife-mcp[lite]"
codex mcp add pseudolife-memory -- pseudolife-mcp
```
Then in either coding agent: *"remember that my staging box is haze-02"* →
the agent calls `memory_store`; next session, *"which box is staging?"* →
`memory_search` finds it. Browse everything at the Cortex Console:
<http://127.0.0.1:8765/ui/>.
The first session auto-starts the daemon, which provisions an **embedded
PostgreSQL 18** (pgvector included, via `pg0-embedded`) under a stable
per-user data dir and downloads the embedding model (~1.2 GB, one-time).
It is a real Postgres bank, not a cut-down one: `pseudolife-mcp backup`
writes a standard owner-free `pg_dump` archive (plus a state archive, 7-day
rotation) that restores into any PostgreSQL 18 target regardless of role —
the Docker tier included — so outgrowing lite is a dump/restore, not a
migration project ([backups](docs/guide/configuration.md#backups)). For a
tier- and Postgres-version-independent copy, `pseudolife-mcp export` /
`import` move the whole bank as portable JSONL
([logical export / import](docs/guide/configuration.md#logical-export--import)).
Windows needs an ASCII-only data path
([`PSEUDOLIFE_MCP_DATA_DIR`](docs/guide/configuration.md#connection--deployment-env-vars)).
### What lite gives you, and the one thing it doesn't
| | lite (pip) | durable (Docker) |
|---|---|---|
| Associative store, hybrid search, supersession, version history | yes | yes |
| Cortex facts, knowledge graph, lessons, world facts, episodes | yes | yes |
| Cortex Console, document RAG, `pseudolife-mcp backup` | yes | yes |
| **Dream consolidation filling the cortex on its own** | **no extractor ships** | yes — bundled local CPU sidecar |
| External volumes, health-checked services, deploy/rollback tooling | no | yes |
**The gap, stated plainly.** Lite ships no **extractor**, so the **dream**
pass still runs, prunes, and advances its **cursor**, but writes no
canonical facts: on this path `memory_fact_set` is the only **cortex**
writer. Everything else above works. Nothing about this is silent —
`curl http://127.0.0.1:8765/health` reports `"extractor": "none"`, and the
stdio shim says the same on stderr at session start.
Any OpenAI-compatible endpoint closes it. The daemon inherits the
environment it starts from, so two variables are the whole fix — with a
local Ollama:
```bash
export PSEUDOLIFE_DREAM_BASE_URL=http://localhost:11434/v1
export PSEUDOLIFE_DREAM_MODEL=qwen2.5:7b
pseudolife-mcp serve
```
```powershell
$env:PSEUDOLIFE_DREAM_BASE_URL = "http://localhost:11434/v1"
$env:PSEUDOLIFE_DREAM_MODEL = "qwen2.5:7b"
pseudolife-mcp serve
```
`/health` then reports `"extractor": "configured"`. One gotcha: a daemon
that is already running keeps the environment it started with, and the shim
reattaches to it rather than spawning a new one — stop the old daemon
first. A hosted endpoint works too, and costs you the zero-egress
property: memory text leaves the machine. Extractor tiers, quality, and the
trade-offs: [Dreaming](docs/guide/dreaming.md).
## Durable tier — Docker (recommended for a long-lived bank)
Everything above plus the bundled extractor, external volumes,
health-checked services, and backup/rollback tooling. Requires Docker and
at least one MCP-capable coding agent — Claude Code, Codex, and Gemini CLI
are wired end-to-end; anything else gets paste-ready config
([provider matrix](docs/guide/providers.md)). One command from clone to
first memory:
```bash
git clone https://github.com/Pseudogiant-xr/Pseudolife-MCP.git
cd Pseudolife-MCP
ops/install.sh # Linux / macOS
ops\install.ps1 # Windows (pwsh 7+)
# Codex: add --client codex / -Client codex
# Both: add --client both / -Client both
# Gemini: add --client gemini — or several: --client claude,codex,gemini
# Other MCP agents (Cursor, Windsurf, Zed, ...): --client generic
```
The installer asks which agents to wire (multi-select, with a capability
matrix showing exactly what each one gets — session briefing, per-turn
discipline, standing file), runs the preflight (one exact fix line per
missing prerequisite), then asks which **dream extractor** should
consolidate memories —
- **sidecar** — the bundled local CPU model; no Claude plan needed, works
for everyone, and keeps every memory on the box (~11.8 GB image);
- **sonnet-only** — the lightest install: a Claude model via a CLI shim
(`claude-opus-5` by default; the mode name is historical. Needs a
logged-in Max-plan `claude` CLI); the sidecar image is **never built or
pulled** (~11.8 GB lighter; dreams pause while the shim is down);
- **sonnet-fallback** — the Claude shim primary, the bundled sidecar as
automatic fallback (Max-plan CLI plus the ~11.8 GB image);
- **codex-only / codex-fallback** — the same two shapes on an OpenAI
subscription: a GPT-5.6 model (Sol / Terra / Luna) via the Codex CLI
shim on a signed-in ChatGPT plan (extraction quality unmeasured — see
the [dreaming guide](docs/guide/dreaming.md)) —
then brings the stack up, installs the selected clients' session hooks
(where the client has a hook system), registers the MCP transport (the
stdio shim by default, with a per-provider writer id; direct HTTP via
`--transport http`), and health-checks the daemon — finishing with a
per-agent ladder of what got wired and what that agent's platform cannot
support. Where a session-hook briefing exists (Claude, Codex off-Windows)
no standing-file edit is needed; for hook-less providers (Gemini CLI,
generic agents, Codex on Windows) the installer offers to append the
standing block instead — there it *is* the briefing. `--instructions
append` always writes the block from `examples/CLAUDE.memory.md` into
`~/.claude/CLAUDE.md` / `~/.codex/AGENTS.md` / `~/.gemini/GEMINI.md`
(useful for subagent visibility even with hooks).
Idempotent — re-run any time; `--extractor <mode>` switches extractor
setups. Non-interactive example:
`ops/install.sh --extractor sidecar --client codex`.
Linux (Docker Engine): your user must be in the `docker` group —
`sudo usermod -aG docker $USER`, then log out/in (the preflight checks this).
Image sizes, the Windows WSL2 memory cap, and what the installer automates:
[the containerized install](#install--containerized-any-os) below.
<details>
<summary>Manual install (the steps the installer automates)</summary>
```bash
ops/preflight.sh --client codex # or ops\preflight.ps1 -Client codex
docker volume create pseudolife-mcp-bank
docker volume create pseudolife-mcp-state
docker compose -f ops/docker-compose.yml up -d --build # first build, once
# ...or pull the prebuilt images instead of building (releases >= 0.14.0):
docker compose -f ops/docker-compose.yml -f ops/docker-compose.ghcr.yml pull pseudolife-pg pseudolife-daemon
docker compose -f ops/docker-compose.yml -f ops/docker-compose.ghcr.yml up -d
# Verify, then wire the transport into one or both clients.
curl http://127.0.0.1:8765/health
# Stdio shim (the installer's default — per-session episode identity).
# PSEUDOLIFE_MCP_NO_SPAWN=1 makes the shim wait for the container instead
# of spawning a host fallback that can shadow the Docker bank after a
# reboot; set it on Docker-tier registrations like these.
pip install pseudolife-mcp
claude mcp add --scope user pseudolife-memory --env PSEUDOLIFE_MCP_NO_SPAWN=1 -- pseudolife-mcp
codex mcp add pseudolife-memory --env PSEUDOLIFE_MCP_NO_SPAWN=1 -- pseudolife-mcp
# ...or direct HTTP (no pip package needed; fine for single-session setups):
claude mcp add --transport http --scope user pseudolife-memory http://127.0.0.1:8765/mcp
codex mcp add pseudolife-memory --url http://127.0.0.1:8765/mcp
# Reinforce the protocol-level memory loop with a global standing instruction:
cat examples/CLAUDE.memory.md >> ~/.claude/CLAUDE.md
cat examples/CLAUDE.memory.md >> ~/.codex/AGENTS.md
# (PowerShell: Add-Content "$env:USERPROFILE\.claude\CLAUDE.md" (Get-Content examples\CLAUDE.memory.md -Raw))
```
Optional knobs live in `ops/.env` (`cp ops/.env.example ops/.env` — the
install/update scripts scaffold it too; every value is commented, a missing
file runs entirely on defaults).
</details>
## What this is
A memory engine exposed over MCP. There's no chat UI and no LLM doing the
thinking — your coding agent is the intelligence; these are tools it calls to store and
recall what matters. (Models *are* bundled as plumbing: baked embedding
weights for retrieval, and the optional CPU extractor sidecar that
consolidates memories into facts while you sleep.)
Where it sits among the common approaches to agent memory — each column
is a fair tool for what it's for; this table is about *what question each
one answers*, not who's wrong:
| | notes file (`CLAUDE.md`) | auto-journaling plugin | plain vector store | Pseudolife-MCP |
|---|---|---|---|---|
| Survives sessions and compactions | yes | yes | yes | yes |
| "What is X *now*?" has one current answer | if you curate it | no — replays what happened | no — every stored version competes at recall | yes — slot-keyed cortex |
| A correction replaces the old value | you edit the file | appended beside it | old and new both retrievable, unranked by recency of truth | supersedes, with full version history kept |
| Facts know their age and go stale | no | no | no | dated, freshness-decayed, quarantined when stale |
| Distils do/avoid lessons from its own outcomes | no | no | no | yes |
| Benchmark numbers ship with their raw run artifacts | — | typically no | typically no | every published number, test-enforced |
Auto-journaling records what the agent *did*; Pseudolife curates what it
*learned*. Both are useful — they answer different questions. Named
alternatives — Mem0, Zep/Graphiti, Letta, Cognee, memU, Memori — and the
cases where one of them is the better pick:
[Comparison](docs/guide/comparison.md).
It layers several complementary stores: the **associative store** (a flat
embedding store ranked by cosine similarity fused with a BM25 lexical pool
(on by default), with contradiction detection and supersession; an 8-tier
banded layout is available as an opt-in preset); the **cortex** (slot-keyed canonical facts — one *current*
value per `entity.attribute`, or a member set for set-valued slots — with
provenance tiers and contender parking instead of silent overwrites); a typed **knowledge graph** over those facts
with a closed relation vocabulary and on-read inference; the **world
cortex** (durable *cited* facts about external reality, age-decayed trust);
**procedural lessons** learned from the agent's own work; and a ChromaDB
**reference bank** for document RAG. The canonical layers in depth:
[the memory model](docs/guide/memory-model.md); the graph and multi-hop
recall: [retrieval](docs/guide/retrieval.md).
State lives in Postgres (the durable source of truth) behind a single
long-lived daemon; every session attaches through a thin stdio shim
(installer default — per-session identity) or directly over HTTP
(single-session setups). The result: Claude can pick up where it left
off, correct itself when facts change, and reason over relationships —
without you re-explaining context each session.
## Documentation
This README is the front door — install, wiring, and the basic loop. The
deep material lives in the user guide:
| Page | What's in it |
|---|---|
| [Configuration](docs/guide/configuration.md) | Env vars, tuned defaults, toolset tiers, stdio shim, LAN sharing, data layout, backups, schema history |
| [Providers](docs/guide/providers.md) | Capability matrix per coding agent, the hook-equivalent ladder, AGENTS.md standard, Codex hooks opt-in, writer ids |
| [Retrieval](docs/guide/retrieval.md) | Reranker, BM25 hybrid, abstention floors, ranking-trace debugging, `memory_recall`, the knowledge graph |
| [Dreaming](docs/guide/dreaming.md) | Extractor tiers, the bundled sidecar, upgrading the extractor, Sonnet-fallback, cadence, deep dream, consolidation |
| [Episodes & sessions](docs/guide/episodes.md) | Daemon-owned session episodes, the briefing hook, nested sub-episodes, tags |
| [The memory model](docs/guide/memory-model.md) | Cortex slots, provenance contenders, world cortex, lessons, temporal/HLC stamps |
| [Benchmarks](docs/guide/benchmarks.md) | LongMemEval results; why extraction quality dominates |
| [Comparison](docs/guide/comparison.md) | Mem0, Zep/Graphiti, Letta, Cognee, memU, Memori — the axes, and when to use something else |
| [Security posture](docs/guide/security-posture.md) | Memory poisoning (ASI06): every shipped mitigation, and what is not defended |
Plus [`evals/README.md`](evals/README.md) (full benchmark methodology) and
[CONTRIBUTING](CONTRIBUTING.md).
## Tools exposed
The surface was consolidated 2026-07-02 (55 → 32 tools; now 35 with
`memory_toolset` and the set-slot pair): lifecycle families became verb-dispatched tools
(`memory_dream`, `memory_forget`, `memory_graph_review`), and
dump/introspection views moved to the Cortex Console (REST) — the manifest
is agent context every session, so it stays lean.
| Tool | Purpose |
|------|---------|
| `memory_store(text, source?, tags?, origin?, episode?, authority?, distortion_tolerance?)` | Remember one durable fact / decision / observation (canonical facts reach the cortex via the dream pass or `memory_fact_set`); `authority`/`distortion_tolerance` label the speech act and how exactly it must survive — `auto` (default) is a deterministic form heuristic, no model call, and both labels are inherited through supersession unless restated |
| `memory_search(query, top_k?, filters..., rerank?, bm25?, explain?, verbose?)` | Associative retrieval; canonical `cortex` facts surface ahead of recall hits, each dated (`asserted_at` / `last_confirmed` / human `age`, plus `stale` when it has rotted); `explain=True` attaches a ranking trace |
| `memory_recent(n?, sources?, episodes?, tags?, verbose?)` | Newest stores, timestamp-ordered (debug + session catch-up) |
| `memory_supersede(old_text, new_text)` | Explicit correction — mark a memory obsolete, keep it as history; the result's `derived_flagged` names the canonical facts the dream built on what was corrected (flagged, never rewritten) |
| `memory_forget(scope, ...)` | Forget from one store: `memory` (by text/substring/source/episode/tag) and `fact` hard-delete; `world` and `lesson` (by entity/attribute) retire the slot with an audit row — reversible via `memory_graph_review(action="restore_slot")` |
| `memory_stats()` | Store occupancy, hit rates, totals |
| `memory_get(entry_id)` / `memory_reinforce(entry_id)` | Dereference a memory id to its full episode (+ `consolidated_into`); reinforce it after finding it useful |
| `memory_fact_get(entity, attribute)` | The one CURRENT canonical value at a slot (+ parked contenders); on an empty slot returns ranked `candidates` (same-entity, then similar slots); aged/contested facts carry a ready-made `correct_with` call (as do `memory_search` / `memory_world_search` hits) |
| `memory_fact_set(entity, attribute, value, origin?, confidence?, episode?, freshness_class?, authority?, distortion_tolerance?)` | Assert a canonical fact deliberately (insert / confirm / supersede / contest); `freshness_class` (`auto` default) says how fast the slot rots — `auto` infers it from the entity's kind; `authority`/`distortion_tolerance` (`auto` = deterministic form heuristic, no model call) inherit the slot's labels unless restated |
| `memory_fact_resolve(entity, attribute, accept)` | Settle a contested slot — adopt (`true`) or discard (`false`) the contender |
| `memory_set_add(entity, attribute, member)` / `memory_set_remove(entity, attribute, member)` | Add/confirm or retract one member of a set-valued slot (many concurrent values, e.g. tags — not one NOW value); a scalar there converts to a set one-way on first `memory_set_add`, except a number-led aggregate scalar ("32", "$1,500"), which is protected — the add parks as a contender instead. Read with `memory_fact_get`, which returns `{kind: "set", members, removed}` for these slots |
| `memory_history(entity, attribute?)` | With `attribute`: version timeline at a slot, with writer/temporal stamps. Without: the entity's causal chain — dated fact/entry/edge/lesson events ("what led to X") |
| `memory_world_set(entity, attribute, value, source_url?, ...)` | Assert a cited WORLD fact (external knowledge; age-decayed trust by freshness class) |
| `memory_world_search(query, top_k?, verbose?)` | Search world facts — each carries `effective_confidence`, a `stale` flag, and its citation |
| `memory_outcome(task, outcome, about?, detail?, polarity?, episode?)` | Record a procedural outcome signal (`success`/`failure`/`correction`); the dream distils signals into lessons |
| `memory_lesson_search(query, top_k?, verbose?)` | Recall learned lessons for the task at hand — heed `polarity` `-` dead-ends; `re_verify` flags lessons whose subject facts changed since |
| `memory_dream(action, limit?, cursor?, apply?, snippets?, run_id?)` | Drive the dream: `status` / `pull` / `commit` / `run` (server-side extractor) / `runs` (audit trail of recent passes) / `rollback` (revert the latest committed pass from its pre-image journal) / `deep` (full-corpus graph consolidation; dry-run unless `apply`, which snapshots the graph tables first; `snippets=false` omits candidate evidence; responses carry evidence-enriched `merge_proposals` for near-duplicate triage) |
| `memory_graph_review(action, proposal_id?, proposal_ids?, proposals?, scope?, src?, dst?, relation?, store?)` | Work the review queue: `list` / `propose` / `relate` (link a pair *and* dismiss its duplicate proposal in one call) / `dismiss_pair` / `dismiss_slot_pair` / `restore_slot` / `accept_link` / `reject_link` / `accept_merge` / `accept_junk` / `reject_entity` (merge/entity decisions are audit-stamped `decided_by=agent` over MCP, `human` via Console); `proposal_ids` settles many id-actions in one call; `restore_slot` undoes a `memory_forget(scope="lesson"/"world")` retirement — `store` + the retired `entity|attribute` key in `src` (or a bare entity to restore every retired aspect) |
| `memory_session_title(title, episode?)` | Name THIS session's auto-opened episode (default titles are generic); `episode` is your session handle from the briefing — concurrent sessions share one HTTP connection, so pass it to land the rename on your own episode |
| `memory_episode_start(title, hint?, episode?)` / `memory_episode_end(episode?)` | Open/close a nested sub-episode for a substantial task; entries stored while open carry its id; `episode` is your session handle so the nest/pop lands in your own tree when several sessions run concurrently |
| `memory_episode_summary(id)` | Stats + tag/source distribution + recent entries within an episode |
| `memory_consolidation_candidates(query?, episode?, ...)` | Cluster near-duplicate memories ripe for consolidation |
| `memory_consolidate(replaces, new_text, source?, tags?)` | Atomic supersede + store — replace a cluster with one canonical note |
| `memory_graph_relate(src, relation, dst, ...)` | Assert a typed edge (closed relation vocabulary; re-assertion bumps confidence) |
| `memory_graph_unrelate(src, relation, dst)` | Retract an edge (superseded, kept for audit) |
| `memory_alias(entity, alias)` | Bind an alternative name — lookups resolve aliases first |
| `memory_graph(entity, depth?, include_facts?, to?, relation_filter?)` | Entity neighborhood (≤3 hops) with derived transitive/inverse edges and per-edge `EXTRACTED/INFERRED/AMBIGUOUS` provenance tags; `to` returns the shortest path between two entities |
| `memory_recall(query, hops?, top_k?, verbose?)` | Multi-hop retrieval for relational questions; `low_confidence: true` → fall back to `memory_search` |
| `memory_relation_define(name, description, ...)` | Grow the closed relation vocabulary (deliberate, rare act) |
| `document_ingest(path, source?)` | Index a file (txt/md/pdf/html) verbatim in the reference bank — the lossless complement to agent-side distillation ([division of labor](docs/guide/memory-model.md#background-documents--the-reference-bank)) |
| `document_search(query, top_k?)` | RAG search over the reference bank only |
| `memory_toolset(action)` | Check or change this principal's visibility tier: `status` / `expand` / `collapse` |
Each tool returns plain JSON. See `pseudolife_memory/mcp_server.py` for
docstrings — those are what Claude reads to decide when to call which tool.
The five recall-path tools return **compact entries** by default (result
payloads are agent context on every retrieval); pass `verbose=true` for full
metadata. Full-table dumps and topology views live in the **Cortex Console**
(`/api/*`) and the `pseudolife-mcp briefing` CLI.
**Toolset tiers.** Three visibility tiers — `minimal` (9 tools), `core`
(22), `full` (35) — filtered per principal at
`tools/list`; a principal (the named bearer-token identity, or the writer
id for single-token installs) steps its own tier up or down with
`memory_toolset` before calling a hidden tool. Defaults, per-client mapping, and weak-model
deployments:
[Configuration — toolset tiers](docs/guide/configuration.md#toolset-tiers).
## Architecture
One **memory daemon** owns the bank and serves MCP over streamable HTTP
at `/mcp`; every Claude Code session (and any LAN agent) attaches to it.
**Postgres 18 + pgvector** (in Docker on the durable tier; the lite tier
runs the same Postgres embedded, no container) is the durable source of
truth —
the in-memory store is a write-through cache hydrated at startup
(a small `weights.pt` persists only counters — there are no MLP weights).
The daemon runs **either** containerized (recommended — portable, no host
Python) **or** as a host process. Claude Code attaches through a thin
torch-free stdio **shim** (the installer default — per-session identity,
needed for concurrent sessions) **or** directly over **HTTP** (simpler for
a single session):
```
Claude session A ─┐ stdio shim (installer default) or HTTP
Claude session B ─┼───────────────────► pseudolife-mcp daemon ─► Postgres (Docker)
LAN agent ────────┘ or stdio shim (single writer) pgvector
(per session) host proc OR Docker
```
This kills two v0.1 hazards by construction: a single writer means
concurrent sessions can't clobber each other, and entries are transactional
so a crash can't wipe the bank. On top of the associative store sit the
canonical layers — cortex, world facts, lessons, temporal/HLC stamps
([the memory model](docs/guide/memory-model.md)) — joined to a typed
knowledge graph walkable via `memory_graph` and multi-hop `memory_recall`
([retrieval & the graph](docs/guide/retrieval.md)).
## Install — containerized (any OS)
What [the durable tier](#durable-tier--docker-recommended-for-a-long-lived-bank)
installer above does, by hand. The whole stack — Postgres **and** the memory daemon — runs in Docker.
No host Python, no torch install, no version skew; the daemon image bakes
in CPU-only torch and the embedding weights — `Qwen/Qwen3-Embedding-0.6B`
(the default retrieval backbone since schema v25) plus `all-MiniLM-L6-v2`
(kept baked for the ONNX-parity test path) — so it runs identically on
Windows / macOS / Linux. Requires only Docker; built once: ~5.0 GB daemon
image (measured 2026-07-29 on the deployed build) + ~0.6 GB Postgres +
~11.8 GB extractor sidecar (measured 2026-08-20 with the v3 multi-task
bake; skip the sidecar entirely with the installer's `sonnet-only` mode).
The ~12.6 GB and ~10.4 GB figures published before
2026-07-29 are retired: both were inflated by a CUDA torch build that a
dependency-resolution bug pulled into the image (see the CHANGELOG); the
daemon has always been CPU-only.
```bash
git clone https://github.com/Pseudogiant-xr/Pseudolife-MCP.git
cd Pseudolife-MCP
# 1. One-time: create the two persistent volumes (bank + daemon state).
docker volume create pseudolife-mcp-bank
docker volume create pseudolife-mcp-state
# 2. Build + start all three services (Postgres, extractor, then the daemon).
docker compose -f ops/docker-compose.yml up -d --build
```
Or skip the ~5 GB daemon build entirely and **pull the prebuilt images**
(releases ≥ 0.14.0):
```bash
docker compose -f ops/docker-compose.yml -f ops/docker-compose.ghcr.yml pull pseudolife-pg pseudolife-daemon
docker compose -f ops/docker-compose.yml -f ops/docker-compose.ghcr.yml up -d
```
The extractor sidecar is not published and still builds locally; updates on
the pull path are `pull` + `up -d`, not `ops/update.ps1`.
> **Upgrading from a pre-rename install** (volumes `ops_pseudolife_pgdata` /
> `ops_pseudolife_data`)? Don't rename those volumes — keep pointing at them by
> creating `ops/.env` with `PSEUDOLIFE_BANK_VOLUME=ops_pseudolife_pgdata` and
> `PSEUDOLIFE_STATE_VOLUME=ops_pseudolife_data` before `up`. See the compose header.
> **Windows:** cap Docker Desktop's WSL2 VM, which otherwise claims up to
> ~50% of host RAM — how much the stack actually needs, the
> `ops/wslconfig.example` template, and the daemon container's own memory
> cap: [Configuration — Windows / WSL2 memory](docs/guide/configuration.md#windows--wsl2-memory-docker-tier).
The daemon serves MCP at `http://127.0.0.1:8765/mcp` and restarts with
Docker — no logon task needed. First build downloads the model into the
image (once); every container start after that is offline and fast. Wire
Claude Code in via the stdio shim (installer default) or directly over
HTTP (both below). Where the data actually lives, and
how to back it up:
[Configuration — data layout](docs/guide/configuration.md#data-layout).
**Host-process install (Windows, for GPU / dev):** run Postgres in Docker
but the daemon on host Python — for hacking on the daemon or running the
embedder on a local GPU. Steps, the `pseudolife-mcp` CLI modes, and the
logon autostart task:
[Configuration — host-process install](docs/guide/configuration.md#host-process-install-windows-for-gpu--dev).
## Updating
**Lite tier:** one command, bank untouched:
```bash
pip install -U "pseudolife-mcp[lite]"
```
**Docker tier:** after a `git pull` (or local code change), redeploy the
**daemon only** — safely, without touching Postgres or the extractor:
```powershell
.\ops\update.ps1 # Windows
```
```bash
./ops/update.sh # Linux / macOS
```
It backs up the bank (`pg_dump` + a state-volume tar), tags a rollback
image (when a previous one exists — it says so loudly when there isn't),
rebuilds + recreates **only** the daemon, and waits for `/health`.
It never runs `down -v`. (Host-process install: just restart the daemon —
`pip install -e .` is editable.) Build cache is pruned automatically after
every healthy deploy; see
[Docker disk retention](docs/runbooks/docker-disk-retention.md) for the
weekly Scheduled Task and the manual `.vhdx` compact. Never run
`docker system prune --volumes`, which deletes volumes.
> **Two upgrades are not automatic**, because neither can be done safely
> in place. Both have a step-by-step runbook — backup, dry run, apply,
> verify, roll back — and a fresh install needs neither:
>
> - **A bank older than 0.11.0 (schema v25)**: every embedding column moved
> from `vector(384)` to `vector(1024)`, so the daemon refuses to start
> rather than half-migrate. Re-embed offline with
> `ops/migrate_embeddings.py` —
> [the v25 migration runbook](docs/runbooks/embedding-v25-migration.md).
> - **A Docker-tier bank created before 2026-08-14 (PostgreSQL 16 → 18)**:
> a Postgres major bump cannot reuse the old data volume. Run
> `pwsh ops/migrate-pg18.ps1` —
> [the PostgreSQL 18 migration runbook](docs/runbooks/postgres-18-migration.md).
## Wire into your coding agent
**Plugin (hooks + commands).** With the daemon running, two commands inside
Claude Code wire the session hooks (briefing + episode identity), the
memory-loop instructions, and the `/dream` + `/memory-status` commands:
```
/plugin marketplace add Pseudogiant-xr/Pseudolife-MCP
/plugin install pseudolife-memory@pseudolife-mcp
```
The plugin replaces the settings.json hook **and** the CLAUDE.md block below
— the same standing instructions arrive as session context from the daemon.
It deliberately does **not** bundle the MCP server: Claude Code loads a
plugin server alongside any user-registered one with no deduplication, which
doubled every session's tool namespace next to the installer's registration
— so the transport is registered exactly once, by `ops/install.*` (stdio
shim by default — per-session episode identity) or the one-liner below.
Details, non-default ports/tokens, and migration:
[plugin/README.md](plugin/README.md).
**Manual transport registration.** The installer's default (shim mode)
registers a thin stdio shim — one shim process per session, so every
session carries its own tier-1 identity. The same wiring by hand:
```bash
pip install pseudolife-mcp # daemon in Docker; add [lite] for the pip tier
claude mcp add --scope user pseudolife-memory --env PSEUDOLIFE_MCP_NO_SPAWN=1 -- pseudolife-mcp
```
`PSEUDOLIFE_MCP_NO_SPAWN=1` belongs on Docker-tier registrations: the shim
then waits for the container instead of spawning a host-side fallback whose
port bind can race a still-booting Docker and shadow the real bank. On the
`[lite]` pip tier drop the `--env` — there the spawn fallback *is* the
zero-config path.
Direct HTTP works too — the daemon serves MCP over HTTP natively (no shim,
no host command, nothing OS-specific; concurrent sessions then share one
episode identity, so it fits single-session setups best):
```bash
claude mcp add --transport http --scope user pseudolife-memory http://127.0.0.1:8765/mcp
```
(`--scope user` registers it for every project; drop it to register for the
current project only.) Or write the equivalent JSON yourself — into
`~/.claude.json` under the top-level `mcpServers` key for user scope, or into
a `.mcp.json` at a project root for project scope:
```json
{
"mcpServers": {
"pseudolife-memory": {
"type": "http",
"url": "http://127.0.0.1:8765/mcp"
}
}
}
```
For a token-protected daemon, add a `headers` key to that Claude JSON entry:
`"headers": { "Authorization": "Bearer <your-token>" }`.
Codex — the installer's default (shim mode) wires the same stdio shim, so a
Codex session gets its own tier-1 identity instead of inheriting a
concurrent Claude session's episode:
```bash
pip install pseudolife-mcp
codex mcp add pseudolife-memory --env PSEUDOLIFE_MCP_NO_SPAWN=1 -- pseudolife-mcp
```
(Same Docker-tier note as the Claude wiring above: keep
`PSEUDOLIFE_MCP_NO_SPAWN=1` when the daemon runs in Docker; drop it on the
`[lite]` pip tier.)
The HTTP one-liner works too (no pip package needed):
```bash
codex mcp add pseudolife-memory --url http://127.0.0.1:8765/mcp
```
Or add the equivalent user-level entry to `~/.codex/config.toml`:
```toml
[mcp_servers.pseudolife-memory]
url = "http://127.0.0.1:8765/mcp"
bearer_token_env_var = "PSEUDOLIFE_MCP_TOKEN"
```
For that Codex HTTP configuration, export `PSEUDOLIFE_MCP_TOKEN` in the
environment that launches Codex. The token stays out of `config.toml`, and
Codex reads it when connecting. This is unnecessary for the default stdio shim.
Gemini CLI — same shape (`-s user` matters: Gemini defaults to project
scope; the `-e` env gives Gemini sessions their own write attribution, and
the same Docker-tier `PSEUDOLIFE_MCP_NO_SPAWN=1` note as above applies):
```bash
pip install pseudolife-mcp
gemini mcp add -s user -e PSEUDOLIFE_WRITER_ID=gemini -e PSEUDOLIFE_MCP_NO_SPAWN=1 pseudolife-memory pseudolife-mcp
```
Or HTTP, no pip package needed:
```bash
gemini mcp add -s user -t http pseudolife-memory http://127.0.0.1:8765/mcp
```
Note: since 2026-06-18 Google no longer serves individual-tier accounts
(free, AI Pro, AI Ultra) through Gemini CLI — OAuth sign-in fails and
points at Antigravity. The wiring above stays correct, but individual
accounts need API-key auth (`GEMINI_API_KEY`) to actually run sessions —
or use Google Antigravity itself, which connects to the same bank via
`~/.gemini/config/mcp_config.json`; both are covered in
[the providers guide](docs/guide/providers.md#gemini-cli).
**Any other MCP-capable agent** (Cursor, Windsurf, Zed, Copilot CLI, …) —
add the generic `mcpServers` entry to that tool's MCP config (`ops/install.sh
--client generic` prints both shapes ready to paste):
```json
{
"mcpServers": {
"pseudolife-memory": {
"command": "pseudolife-mcp",
"env": {
"PSEUDOLIFE_WRITER_ID": "mcp-client",
"PSEUDOLIFE_MCP_NO_SPAWN": "1"
}
}
}
}
```
What each agent gets — and what its platform can't support (hooks,
per-turn discipline): [the provider matrix](docs/guide/providers.md).
**Verify:** run `claude mcp list`, `codex mcp list`, or `gemini mcp list`
(the server should report connected), then ask the agent to *"store a memory
that this install works"* and check it
appears in the Stream tab of the Console at <http://127.0.0.1:8765/ui/>.
Preferring stdio (this is what the installer wires by default, for
per-session identity)? A thin torch-free **shim** proxies stdio to the
daemon:
[stdio shim](docs/guide/configuration.md#stdio-shim-per-session-identity)
· [LAN sharing](docs/guide/configuration.md#sharing-memory-on-the-lan)
· [backups & restore rehearsal](docs/guide/configuration.md#backups).
## Recommended agent setup (CLAUDE.md / AGENTS.md)
The server's value depends entirely on the agent *using* it well — **this step
is what makes the memory loop actually fire**. The MCP server advertises the
core loop through protocol-level `instructions`, and the session hook (one
command, below) delivers the full block every session — **plugin users and
hook users need nothing more**. If you want it in a standing file instead —
or additionally, for subagent visibility (subagents read `CLAUDE.md` but not
hook output) — append it to Claude's global `~/.claude/CLAUDE.md`, Codex's
global `~/.codex/AGENTS.md`, Gemini's global `~/.gemini/GEMINI.md`, or a
per-project `CLAUDE.md` / `AGENTS.md`:
```bash
cat examples/CLAUDE.memory.md >> ~/.claude/CLAUDE.md
cat examples/CLAUDE.memory.md >> ~/.codex/AGENTS.md
cat examples/CLAUDE.memory.md >> ~/.gemini/GEMINI.md
```
```powershell
Add-Content "$env:USERPROFILE\.claude\CLAUDE.md" (Get-Content examples\CLAUDE.memory.md -Raw)
Add-Content "$env:USERPROFILE\.codex\AGENTS.md" (Get-Content examples\CLAUDE.memory.md -Raw)
```
For hook-less providers this standing block is not a nice-to-have — it *is*
the session briefing. `AGENTS.md` is the cross-vendor standard for standing
agent instructions (Linux Foundation-governed; read by Codex, Copilot,
Cursor, Gemini CLI, Zed, and 30+ others), so a per-project `AGENTS.md`
carrying the block reaches almost every agent at once. Claude Code is the
holdout — it reads `CLAUDE.md` — but a `CLAUDE.md` whose first line is
`@AGENTS.md` imports the shared file, so one copy serves every tool.
The block ([`examples/CLAUDE.memory.md`](examples/CLAUDE.memory.md)) teaches
the loop: **RECALL at the start** (`memory_search` / `memory_lesson_search` /
`memory_fact_get` / `memory_world_search`), **CAPTURE as you go**
(`memory_store` with an honest `origin`, `memory_fact_set` for canonical
facts, `memory_world_set` for cited external facts, `source="status"` for
verbose logs so they stay out of the dream), **REFLECT at the end**
(`memory_outcome` — the dream distils these signals into the lessons
surfaced at your next session start).
One command — `ops\install-hook.ps1 -Client codex` (Windows, PowerShell 7) or
`ops/install-hook.sh --client codex` (Linux/macOS) — installs the
**SessionStart briefing hook** for the selected client (what your memory is
unsure about + lessons from past work + verified world facts + where we left
off, injected at every session start) and, for the Claude client, a
**UserPromptSubmit discipline hook**: a static one-line memory reminder on
every turn — recall before reviewing code, docs, or PRs, then compare memory
against the files; status questions are memory questions; log outcomes.
(Codex is excluded from the per-turn hook: its per-prompt hook support is
unverified, and every new Codex hook needs a manual trust review.) The
installer backs up `~/.claude/settings.json`
or `~/.codex/hooks.json` and is idempotent. The manual hook JSON,
the briefing budget flags, and how session episodes open/close/resume
without any hooks: [Episodes & sessions](docs/guide/episodes.md).
**Codex hooks are experimental and off by default** (and not available on
Windows — use the standing AGENTS.md block there). Writing `hooks.json` is
not enough on its own; first enable the hook engine in `~/.codex/config.toml`:
```toml
[features]
codex_hooks = true
```
**Codex hook trust:** Codex also skips every new or changed hook until you
review and trust its exact definition. After installing the Codex hook, start
Codex, open `/hooks`, review the definition from `~/.codex/hooks.json`, and
approve it. Until then, MCP tools still work and the server-level
`instructions` still load, but the richer session briefing is not injected.
## Usage patterns
**At session start** — loads what you've worked on before, persistent
across compactions:
```
memory_search("project context for X")
```
**During work** — store real decisions; skip fleeting chatter (the shipped
store gate is permissive, so deliberate, durable claims only):
```
memory_store("Decided to use stdio transport for the MCP because no port conflicts", source="pseudolife")
```
**When corrected** — marks the old fact superseded *and* stores the
correction; both surface in future retrieval, the new one ranked higher:
```
memory_supersede(
"Provider interface uses synchronous calls",
"Provider interface uses async calls — sync version was the v0.7 prototype only"
)
```
**Hygiene** — `memory` and `fact` scopes hard-delete (at least one filter
is required for scope `memory`, preventing accidental wholesale deletion);
`lesson` and `world` scopes retire the slot with an audit row and are
reversible with `memory_graph_review(action="restore_slot", store=...,
src="entity|attribute")`; for "keep the history but mark it wrong" use
`memory_supersede` instead:
```
memory_forget(scope="memory", source="test-noise")
memory_forget(scope="fact", entity="test-entity")
```
**Discovering what's in the bank:** open the Cortex Console — sources, tags,
episodes, and full-table views all live there. Going deeper:
[reranking, BM25, abstention, and trace debugging](docs/guide/retrieval.md)
· [episodes + tags](docs/guide/episodes.md#episodes--tags)
· [canonical facts, contenders, world facts, lessons](docs/guide/memory-model.md)
· [the consolidation workflow](docs/guide/dreaming.md#consolidation-workflow-agent-driven-dedup).
## Dreaming — consolidating memories into facts
A **dream** distils the recent associative stream into canonical cortex
facts while you're not looking: pull unconsolidated memories → extract
`(entity, attribute, value)` → advance a cursor so nothing is reprocessed.
Extraction is pluggable:
| Tier | How it runs | Needs | Quality |
|------|-------------|-------|---------|
| **0 — none** | no extractor configured — the dream still runs, prunes, and advances its cursor, but writes no canonical facts | nothing | none (`memory_fact_set` is your only cortex writer) |
| **1 — agent-driven** | the **agent itself** is the gateway: the `/dream` judgment session (its manual-extraction branch fires only when no endpoint is configured) | the agent you already run | highest |
| **2 — shipped default** | daemon auto-sweep → the bundled CPU sidecar, or any OpenAI-compatible endpoint | nothing (sidecar) | high; free if local |
The stack ships tier 2 preconfigured (the bespoke Gemma 4 E4B extractor
fine-tune in a llama.cpp sidecar, internal-only). The sweep cadence,
pointing dreams at a bigger local model or at Claude Sonnet with automatic
sidecar fallback, the full-corpus **deep dream** graph pass, and the
privacy/cost trade-offs: [Dreaming](docs/guide/dreaming.md).
## Benchmarks
The headline is the **whole benchmark, not a slice**: all six
[LongMemEval](https://arxiv.org/abs/2410.10813) question types, 500
questions, oracle variant, run end to end through the memory (qwen-27b
extraction under the v25 embedding backbone, BM25-on turn retrieval).
Single pass, graded by the local Qwen3.6-27B bench judge (2026-08-03):
| arm | accuracy | context tokens/question |
|-----|----------|------------------------|
| naive RAG (top-6 turns) | 0.688 | ~1210 |
| cortex facts only | 0.416 | **~158** |
| hybrid (facts + top-3 turns) | 0.664 | ~842 |
| **commit-gated cascade** | **0.690** | ~883 |
The **cascade** is a serving policy, not a fourth pipeline: answer from
the consolidated facts when that channel *commits*, fall back to raw-turn
RAG when it abstains. Overall this is **a wash on accuracy at ~73% of the
context** — 0.690 vs 0.688 is one question in 500 on a single pass, and
nobody should read it as a win. The fact spine alone answers at ~13% of
RAG's token budget, at a large accuracy cost outside the types it is built
for. The structure is per type:
| question type | n | naive RAG | commit-gated cascade |
|---|---:|---:|---:|
| knowledge-update (facts change) | 78 | 0.859 | ~~0.936~~ (retired — [why](docs/guide/benchmarks.md#the-knowledge-update-slice-78-of-the-500)) |
| single-session-user | 70 | 0.929 | 0.943 |
| single-session-assistant | 56 | 0.911 | 0.929 |
| single-session-preference | 30 | 0.800 | 0.700 |
| temporal-reasoning | 133 | 0.526 | 0.526 |
| multi-session | 133 | 0.504 | 0.474 |
The consolidated spine helps where a fact changes and where the answer
sits inside one session; it loses where the answer must be aggregated
across sessions or ordered in time, because per-fact consolidation is
exactly what discards that structure. BEAM-100K reproduces the same shape
independently. Its abstention questions are where the spine looks best —
the fact-spine arm scores 0.950 against naive RAG's 0.775, identical under
the local judge and under an independent Opus-class judge — but the
2026-09-02 five-arm run bounds that reading: a no-memory arm scores 1.000
there, so the edge is calibration (a small fact context refuses where raw
turns confabulate), not evidence that the memory recalled anything. Setup, caveats,
both bench stacks side by side, and the evidence that extraction quality is
the dominant factor: [Benchmarks](docs/guide/benchmarks.md); full
methodology: [`evals/README.md`](evals/README.md).
Retrieval itself was re-measured on the same corpus before the v25 backbone
swap (150 questions, 74,183 haystack turns, 299 gold turns; pure recall — no
reader, no judge): `Qwen/Qwen3-Embedding-0.6B` reaches **R@10 0.809** against
`bge-base-en-v1.5`'s 0.742 and the previously-shipped `all-MiniLM-L6-v2`'s
0.572, and beats bge-base head-to-head **+32/−12 at k=10 (p=0.004)**.
Artifacts: [`embedder-recall-shootout-20260727.json`](evals/results/embedder-recall-shootout-20260727.json),
[`embedder-recall-qwen-vs-bge-20260728.json`](evals/results/embedder-recall-qwen-vs-bge-20260728.json).
## Cortex Console (web UI)
An operator dashboard served by the daemon itself — point a browser at
**`http://127.0.0.1:8765/ui/`** (the `/health` and `/mcp` endpoints are
unchanged; the console is additive). It's a read-mostly instrument panel for
seeing and steering the memory a human otherwise can't observe:
**Observatory** (health, per-layer counts, the memory store's capacity meter, dream
gauges), **Cortex** (canonical facts with provenance, version-history
timelines, inline Accept/Discard for contested slots), **World / Lessons /
Episodes**, **Stream** (live search with rerank/BM25 toggles and a
ranking-trace debugger), **Graph** (interactive force-directed visualiser, with a review drawer that
can Accept/Reject merges or — for a source file and its own bare concept,
`band.py` ↔ `band` — record an `implements` edge instead of forcing
merge-or-dismiss; proposals a background dream has already judged carry a
verdict chip — accept/reject/leave with confidence, the model's reason in
the tooltip — as a lead, never a decision), and **Console** (every safe `config.yaml` scalar with live-vs-restart
badges, diff-preview, and atomic save).
**Auth** mirrors `/mcp`: `/ui` (static shell) and `/health` are open; `/api/*`
requires the same `PSEUDOLIFE_MCP_TOKEN` bearer when one is set (the console
prompts for it and stores it locally). No build step, no CDN, fully offline —
vanilla ES modules + vendored OFL fonts served straight from the daemon.
Developing the UI? A fixture-backed dev server (no Postgres, no torch)
renders the real frontend against canned data:
`python -m pseudolife_memory.web.devserver` → `http://127.0.0.1:8770/ui/`.
Its payloads self-announce (`"fixtures": true` on `/health`), and the
topbar shows a "DEMO DATA — fixture server, not a real bank" chip in
place of the live chip, so a fixture run is never mistaken for a real
bank.
## Capabilities at a glance
| Capability | Status |
|---|---|
| Transport | Streamable-HTTP MCP daemon (`/mcp`); stdio shim is the installer default (per-session identity) — HTTP remains for single-session setups |
| Storage | Postgres 18 + pgvector (source of truth); ChromaDB for the reference bank |
| Associative store | Flat similarity store (default since the 2026-08-15 measured verdict; the 8-tier banded preset remains opt-in); hybrid dense + BM25 ranking (BM25 on by default); contradiction detection and supersession, including a deterministic slot-identity path that fires regardless of embedding similarity |
| Canonical-fact cortex | Single-writer: LLM dream pass + `memory_fact_*` (regex auto-promote opt-in, default off) |
| Set-valued slots | `memory_set_add` / `memory_set_remove` for many-current-value slots; one-way scalar→set conversion, aggregate scalars guarded (park as contender) |
| Provenance contenders | Tier-rank guard `user > action > agent`; `memory_fact_resolve` |
| Fact currency | Every cortex fact is dated (`asserted_at` / `age`); `freshness_class` (`evergreen` / `slow` / `volatile`) decays `effective_confidence` and flags `stale`. Left `auto`, the class is inferred from the entity's kind (schema v24 `entity_kinds`) — only `system` entities can rot; artifacts and concepts stay evergreen |
| Write-time labels | `authority` (`directive` / `observation` / `quoted` — the speech act, orthogonal to the `origin` tier) and `distortion_tolerance` (`constraint` / `procedural` / `belief` / `preference` / `episodic`) on entries and facts, set at write time (explicit, or a deterministic heuristic under `auto`) and inherited through supersession unless restated. A `constraint` source is carried verbatim through the dream (with a post-dream guard) and pinned ahead of cosine in `memory_search`'s cortex block and `memory_recall` when the query names its entity; a `quoted` source is low-trust for the two-man rule (schema v35) |
| Knowledge graph | Typed entities/edges, closed relation vocab, on-read closure (Postgres + NetworkX, no AGE/Cypher) |
| World cortex | `memory_world_*` — cited external facts + age-decayed freshness (manual ingest) |
| Procedural memory | `memory_outcome` (signals) → dream-synthesised lessons via `memory_lesson_search`; `prefers`/`avoids` graph edges; single-writer |
| Sense of time + multi-writer | Per-write stamp (tx/valid time, HLC ordering, writer/session); `memory_history`; relative `age` on reads; `write_mode` seam (snapshot live, occ Phase-2) |
| Episodes + tags | Session episodes daemon-owned, keyed by a resolved five-tier session identity; hook/shim eager-open or lazy-open + idle reaper + prune-empty + resume-after-reap; nested sub-episodes with subtree-expanded recall; multi-valued `tags=[...]` |
| Session briefing | SessionStart hook injects unsure-graph + lessons + verified world facts + last-session recap (`pseudolife-mcp briefing`) |
| Consolidation | `memory_consolidation_candidates` + `memory_consolidate` |
| Optional components | Cross-encoder reranker (`rerank=True`, ~80 MB); ONNX embedding backend (`pip install .[onnx]` — ~3x faster CPU encode, bit-identical, auto-enabled when installed; the default Qwen3-Embedding-0.6B has no ONNX export and falls back to torch, so this currently only speeds up MiniLM-family models); NLI contradiction scorer (`pip install .[nli]`, ~278 MB) |
| Web console | Cortex Console at `/ui/` — health/stats, fact review + history, graph visualiser, search/trace, config editor (read-mostly, token-gated like `/mcp`) |
| Schema version | v37 (Postgres meta version) — additive `ADD COLUMN IF NOT EXISTS` migrations on daemon start, **except v25**: the `vector(384)`→`vector(1024)` move is not additive, so the daemon refuses to start against an older-dimensioned bank until you run [`ops/migrate_embeddings.py`](docs/runbooks/embedding-v25-migration.md); legacy file-mode `.pt` banks auto-migrate into Postgres; [full version history](docs/guide/configuration.md#schema-version-history) |
## Troubleshooting
Start with `curl http://127.0.0.1:8765/health` — it reports the schema
version, storage backend, auth state, and `persist_errors` (non-zero means
writes are failing to reach Postgres; check `docker logs
pseudolife-mcp-daemon`).
- **The cortex stays empty** (canonical facts never appear on their own).
`/health` reporting `"extractor": "none"` means no extractor is
configured, so the dream writes no facts and `memory_fact_set` is the
only cortex writer — expected on the lite tier. Point the daemon at an
OpenAI-compatible endpoint
([Quickstart](#what-lite-gives-you-and-the-one-thing-it-doesnt)) or use
the Docker tier's bundled sidecar. `"extractor": "disabled"` instead
means dreaming itself is switched off in config.
- **Lite daemon refuses to start on Windows** with a message about the data
path: the embedded Postgres runtime needs an **ASCII-only** data
directory. Set `PSEUDOLIFE_MCP_DATA_DIR` to one (e.g.
`C:\pseudolife-data`) —
[Configuration](docs/guide/configuration.md#connection--deployment-env-vars).
- **First build is slow / big.** The daemon image (~5.0 GB, several
minutes to build) bakes in CPU torch and the embedding weights (Qwen3-Embedding-0.6B
plus MiniLM); the extractor sidecar
adds a ~5.3 GB model download on its first build. Every start after that is
offline and fast — if a *rebuild* is re-downloading models, the Docker
layer cache was pruned.
- **Daemon unreachable after `wsl --shutdown`** (Windows): the host port
forward is gone — `docker restart pseudolife-mcp-daemon` re-establishes it.
- **Docker eating RAM** (Windows): the WSL2 VM (`Vmmem`) claims up to ~50% of
host memory by default. Copy `ops/wslconfig.example` to
`%USERPROFILE%\.wslconfig`, tune `memory=`, then `wsl --shutdown`.
- **Port already in use**: the stack binds `127.0.0.1:8765` (daemon) and
`127.0.0.1:5433` (Postgres). Change the host side in
`ops/docker-compose.yml` if either collides.
- **Console shows "offline" / Unauthorized**: "offline" means the daemon
isn't reachable (see above); a 401 prompt means it runs with
`PSEUDOLIFE_MCP_TOKEN` — paste that token into the Console's Token dialog.
- **The coding agent doesn't see the tools**: `claude mcp list` or
`codex mcp list` should show
`pseudolife-memory` ✓ connected. If not, re-check the URL
(`http://127.0.0.1:8765/mcp` — the `/mcp` path matters) and the bearer
header when a token is set. The daemon preloads the embedder on a warmup
thread at start (~5–10 s); a very early first call can race it and take a
few seconds.
- **Tools vanish after an upgrade / the client log says "Connection
closed"**: the shim's registered command can live outside the repo venv,
and the MCP SDK v2 migration set an `mcp>=2.1` floor — an older SDK in
that environment crashes the shim on start. The shim detects this and
prints the interpreter path and the exact fix on stderr: `pip install -U
"mcp>=2.1,<3"` in that interpreter, or re-run the installer (which
registers the project venv's shim).
- **A harness "removed tools" notice is not an outage.** A resumed session
can carry a larger tool roster in its transcript than the current
[toolset tier](docs/guide/configuration.md#toolset-tiers) serves —
that's a visibility filter, not a disconnect. Make one `memory_search`
call before concluding the MCP is down.
## Uninstall
**Lite tier:** remove the MCP registration (`claude mcp remove
pseudolife-memory` / `codex mcp remove pseudolife-memory`), then
`pip uninstall pseudolife-mcp`. If you also want the bank gone, delete
the per-user data directory (`%LOCALAPPDATA%\pseudolife-mcp` on Windows,
`~/.local/share/pseudolife-mcp` on Linux, `~/Library/Application
Support/pseudolife-mcp` on macOS — or wherever `PSEUDOLIFE_MCP_DATA_DIR`
points). Back it up first: `pseudolife-mcp backup` works on lite too.
**Docker tier** — deletion is deliberate at every step:
```bash
# 1. Optional: take a final backup first (ops/backup.ps1 or ops/backup.sh).
# 2. Stop and remove the containers (volumes survive this).
docker compose -f ops/docker-compose.yml down
# 3. Remove the MCP registration.
claude mcp remove pseudolife-memory
codex mcp remove pseudolife-memory
gemini mcp remove pseudolife-memory -s user
# 4. Only when you're sure: delete the data volumes (THIS is the memory).
docker volume rm pseudolife-mcp-bank pseudolife-mcp-state
```
Host-process installs: also unregister the logon task
(`Unregister-ScheduledTask -TaskName "Pseudolife-MCP Daemon"`) and remove
the SessionStart briefing hook — plus, Claude client, the UserPromptSubmit
discipline hook — from `~/.claude/settings.json` and/or
`~/.codex/hooks.json` (a timestamped `.bak-*` sits next to each edited file).
## Testing
`pip install -e .[dev]`, then `pytest tests/`. The suite covers every
layer, from the MemoryService surface to the Cortex Console REST API;
model-heavy pieces are stubbed so it stays fast and offline. The PG-backed
suites each target a throwaway per-run `pseudolife_memory_test_<pid>`
database on the bundled dev container (never your real bank; concurrent
runs can't collide), dropped on exit, and skip cleanly without Postgres.
Full dev setup: [CONTRIBUTING](CONTRIBUTING.md).
## What's not built yet
- **Reflection via MCP sampling** — would let the dream borrow *Claude
itself* as the extractor;
[Claude Code doesn't yet support it](https://github.com/anthropics/claude-code/issues/1785).
- **Cross-machine sync** — memory lives on one PC's disk; syncing via
rclone / syncthing is left as an exercise.
- **Automated world-knowledge ingestion** — populating the world cortex
from the live web needs a web-fetch tool the standalone server doesn't
ship; an agent with web access can automate the fetch+cite step today
via `memory_world_set`.
## Support
**Solo-maintained, best-effort.** One person builds, tests, and runs this;
there is no support contract and no response-time commitment. That said,
issues are read and most get an answer.
- **Something is broken** → open a
[bug report](https://github.com/Pseudogiant-xr/Pseudolife-MCP/issues/new?template=bug_report.yml).
The form asks for your `/health` output, schema version, install tier,
and client, because those four answer most questions before any
back-and-forth