SuperMemory
MCP-first agent learning: capture failures, validate lessons, retrieve context, improve.
Open source Open in the app JSON README (API)
About
MCP-first agent learning: capture failures, validate lessons, retrieve context, improve.
Details
- Kind
- MCP servers
- Topic
- No topic detected
- Publisher
- yashvanthange
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 0.2.5
- Stars
- 2
- Last push
- 2026-06-13T22:16:53Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-29 03:02:21
- Updated
- 2026-08-29 03:02:21
- Origin id
io.github.YashvantHange/supermemory
README
# SuperMemory
<!-- mcp-name: io.github.YashvantHange/supermemory -->
**MCP-first agent learning layer** for Claude, Cursor, and custom agent workflows.
SuperMemory captures **distilled lessons** from failures and corrections — not full conversation transcripts — validates them before storage, and improves agents over time through a closed-loop cycle.
[](https://pypi.org/project/supermemory-agent/)
[](https://github.com/YashvantHange/SuperMemory/releases)
[](LICENSE)
[](https://registry.modelcontextprotocol.io)
---
## Quick start
```bash
pip install supermemory-agent
supermemory-agent --storage .supermemory --transport stdio
```
Or with [uv](https://docs.astral.sh/uv/):
```bash
uvx supermemory-agent --storage .supermemory --transport stdio
```
**Latest release:** [v0.2.4](https://github.com/YashvantHange/SuperMemory/releases/tag/v0.2.4) — wheel + sdist attached on every [GitHub Release](https://github.com/YashvantHange/SuperMemory/releases).
---
## What you get
| Component | Description |
|-----------|-------------|
| **MCP server** | 29 tools + 4 resources over stdio (or streamable HTTP) |
| **Agent skill** | `skills/supermemory-agent-learning/SKILL.md` — bundled in the PyPI package |
| **Python SDK** | In-process integration via `uall_python` |
| **REST API** | FastAPI server for remote / polyglot clients |
| **Storage** | Local `.supermemory/` files by default; SQLite and PostgreSQL optional |
Everything lives in one repo: MCP server, skills, SDK, REST API, tests, and release packages.
---
## Install
### PyPI (recommended)
```bash
pip install supermemory-agent
```
After install, bundled skills are at `site-packages/skills/supermemory-agent-learning/`. Copy to your editor skills folder if needed.
### GitHub Release (offline / pinned version)
Each release ships installable assets:
```bash
pip install https://github.com/YashvantHange/SuperMemory/releases/download/v0.2.4/supermemory_agent-0.2.4-py3-none-any.whl
```
Browse all versions: [github.com/YashvantHange/SuperMemory/releases](https://github.com/YashvantHange/SuperMemory/releases)
### From source (developers)
```bash
git clone https://github.com/YashvantHange/SuperMemory.git
cd SuperMemory
pip install -e ".[dev]"
python -m pytest tests/ -v
```
---
## Configure MCP
### Cursor
Copy `examples/cursor.mcp.json` to `.cursor/mcp.json` in your project:
```json
{
"mcpServers": {
"supermemory": {
"command": "supermemory-agent",
"args": ["--storage", ".supermemory", "--transport", "stdio"]
}
}
}
```
### Claude Desktop
Merge `examples/claude_desktop_config.json` into:
```
%APPDATA%\Claude\claude_desktop_config.json
```
Restart Claude Desktop after saving.
### Run manually
Do **not** run `supermemory-agent` alone in a terminal — stdio mode expects JSON-RPC from an MCP client. Pressing Enter in the shell causes a JSON parse error.
```bash
# For local HTTP testing only:
supermemory-agent --transport streamable-http
```
When configured in Cursor or Claude Desktop, the client launches the server automatically over stdio.
---
## Agent skills (Cursor + Claude Code)
| Source | Path |
|--------|------|
| **Canonical** (edit here) | `skills/supermemory-agent-learning/` |
| **Cursor project** | `.cursor/skills/supermemory-agent-learning/` |
| **Claude Code project** | `.claude/skills/supermemory-agent-learning/` |
| **PyPI install** | `site-packages/skills/supermemory-agent-learning/` |
After editing `skills/`, sync copies:
```bash
python scripts/sync_skills.py
```
Mention **SuperMemory**, **agent learning**, or **MCP memory** in chat to load the skill.
---
## Learning loop
```
retrieve → record_failure → reflect(event_ids) → validate → process_promotions
→ retrieve again → report_outcome
```
**Core rule:** capture workflow outcomes and distilled lessons only — never full transcripts. Default retrieval budget: `max_tokens=800`.
---
## MCP tools (29)
**Core (13):** `retrieve`, `record_event`, `record_failure`, `record_correction`, `reflect`, `validate`, `process_promotions`, `report_outcome`, `get_policies`, `add_policy`, `add_skill`, `search_skills`, `get_skill`
**Extended UALL (16):** `learn.run.start`, `learn.run.event`, `learn.run.end`, `learn.store`, `learn.retrieve`, `learn.reflect`, `learn.validate`, `learn.evaluate`, `learn.feedback`, `learn.improvements`, `learn.analytics`, `learn.policies`, `learn.experiment`, `learn.rollback`, `learn.skills`, `learn.telemetry`
All tools include MCP safety annotations (`readOnlyHint` / `destructiveHint`).
## MCP resources (4)
- `supermemory://policies/active`
- `supermemory://lessons/{lesson_id}`
- `supermemory://memory/{lesson_id}/provenance`
- `supermemory://skills/{skill_id}`
---
## Python SDK
```python
from uall_python import UALLClient
client = UALLClient(storage="file")
with client.run(workflow_id="pdf-pipeline", step="planner", namespace="team:eng") as run:
lessons = run.retrieve(step="planner", max_tokens=800)
run.record_failure(snippet="chose OCR for searchable PDF", tags=["routing"])
run.report_lesson_outcome(lesson_id="lesson_001", used=True, accepted=True, improved=True)
```
## REST API
```bash
python -m uall_server
```
Server: `http://localhost:8000` — see `api/openapi.yaml`.
---
## Storage
| Tier | Backend | Config |
|------|---------|--------|
| Default | `.supermemory/` JSON files | `SUPERMEMORY_STORAGE_PATH` or `UALL_DATA_DIR` |
| Optional | SQLite | `UALL_STORAGE_BACKEND=sqlite` |
| Enterprise | PostgreSQL | `UALL_STORAGE_BACKEND=postgres` |
---
## Project layout
```
SuperMemory/
├── src/supermemory_mcp/ # MCP server (29 tools, 4 resources)
├── skills/supermemory-agent-learning/ # Agent skill (SKILL.md)
├── packages/uall/ # Core learning engine
├── packages/uall_python/ # Python SDK
├── packages/uall_server/ # REST API
├── examples/ # Cursor + Claude Desktop MCP configs
├── tests/ # 74 tests incl. stdio MCP transport
└── docs/ # Publishing, releases, privacy
```
---
## Tests
```bash
python -m pytest tests/ -v
python -m pytest tests/test_mcp_server.py -v # real stdio MCP transport
python -m pytest tests/test_core.py -v # closed-loop integration
```
---
## Docs
| Doc | Purpose |
|-----|---------|
| [docs/GIT_SETUP.md](docs/GIT_SETUP.md) | Fix commit author name/email on GitHub |
| [docs/RELEASES.md](docs/RELEASES.md) | Release checklist — every tag ships wheel + sdist |
| [docs/PUBLISHING.md](docs/PUBLISHING.md) | PyPI, MCP Registry, Cursor & Claude directories |
| [PRIVACY.md](PRIVACY.md) | Privacy policy |
| [skills/README.md](skills/README.md) | Agent skill install paths |
**MCP Registry name:** `io.github.YashvantHange/supermemory`
**PyPI package:** `supermemory-agent`
---
## License
MIT — see [LICENSE](LICENSE)