io.github.Sandeeprdy1729/timps-swarm
161 AI agents for code gen, health, AI/ML, infra, India-stack. One command.
Open source Open in the app JSON README (API)
About
161 AI agents for code gen, health, AI/ML, infra, India-stack. One command.
Details
- Kind
- MCP servers
- Topic
- Government & public data
- Publisher
- sandeeprdy1729
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 2.2.3
- Stars
- 1
- Forks
- 1
- Last push
- 2026-09-02T08:08:44Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-29 03:02:13
- Updated
- 2026-08-29 03:02:13
- Origin id
io.github.Sandeeprdy1729/timps-swarm
README
<div align="center">
<img src="https://img.shields.io/badge/TIMPS%20SWARM-v2.2-FF6B35?style=for-the-badge&labelColor=1a1a1a" alt="TIMPS Swarm" />
**One `install-mcp` command puts 161 AI specialists into every coding tool you use — as parallel sub-agents, not just MCP tools.**
[](https://www.npmjs.com/package/timps-swarm)
[](LICENSE)
[](https://python.org)
[](https://modelcontextprotocol.io)
[](https://discord.gg/MmsTNm8WF6)
[Quick Start](#quick-start) · [Sub-agents](#what-install-actually-does) · [161 Agents](#the-161-agents) · [MCP Setup](#mcp-integrations) · [CLI](#cli) · [Architecture](#architecture)
</div>
---
*4 agents dispatched in parallel vs sequential — 3× speedup (64s vs 192s)*
## What it does
- **Security audit any repo in 30 seconds** — `npx timps-swarm audit ./` finds CVEs, hardcoded secrets, and OWASP issues. No backend, no config, no API key.
- **161 specialist agents in every AI tool** — one `install-mcp` command writes the MCP config for 9 IDEs (Claude Code, Cursor, Windsurf, Continue, Aider, Cline, Zed, VS Code, Gemini, Codex, Amp, Warp) **and** registers every agent as a native sub-agent so Claude Code / Cursor / Codex can dispatch them in parallel via `Task(subagent_type=...)`.
- **Local-first, BYOK** — runs on Ollama with zero API cost; plug in Gemini/Anthropic/OpenAI/Groq when you want more power.
- **Works without the Python backend** — `npm install -g timps-swarm` ships a Node.js MCP stdio proxy (`cli/lib/mcp-proxy.js`) that talks to any running FastAPI server (local or remote via `TIMPS_API_URL`). The Python repo is optional.
---
## Quick Start
```bash
npm i -g timps-swarm
```
> **Hand this repo to any coding agent and it will set itself up.**
> `SETUP.md` is written as an instruction set (not just docs) — when a user
> clones the repo and tells Claude Code, opencode, Codex, Cursor, Windsurf,
> or any other agent to "read SETUP.md and set me up", the agent installs the
> backend, registers the `timps-swarm` MCP server for whatever tool it's
> running in, and starts dispatching the 161 specialist agents in parallel.
Then wire it into your coding agents:
```bash
npx timps-swarm install-mcp
```
`install-mcp` auto-detects every AI tool on your machine and:
1. Writes the `timps-swarm` MCP server entry into every detected IDE config (with an explicit `env:` block forwarding `ANTHROPIC_API_KEY`, `OPENAI_API_KEY`, `GEMINI_API_KEY`, `GROQ_API_KEY`, `TIMPS_API_URL`, `OLLAMA_HOST`, `REDIS_URL`).
2. Writes one sub-agent `.md` file per TIMPS tool into `~/.claude/agents/`, `./.claude/agents/`, and `~/.codex/agents/`.
Restart your tool — 161 agents appear as MCP tools **and** as parallel sub-agents.
**Run without installing (zero setup):**
```bash
npx timps-swarm audit ./ # security scan any repo — works immediately
```
---
## What install actually does
`install-mcp` is the only command you need:
```bash
npx timps-swarm install-mcp # default: configure all detected tools
npx timps-swarm install-mcp --no-sub-agents # MCP config only, skip the .md files
npx timps-swarm install-mcp --tool cursor # configure one tool
npx timps-swarm install-mcp --dry-run # preview without writing
npx timps-swarm uninstall-mcp # remove all of the above
```
By default this writes:
- **MCP server entries** into 9 IDE config files (one entry per IDE, all pointing at `npx timps-swarm mcp`).
- **161 sub-agent `.md` files** into `~/.claude/agents/`, `./.claude/agents/`, `~/.codex/agents/` (one per MCP tool) so Claude Code's `Task(subagent_type="timps_kubernetes_navigator")`, Cursor Composer, and Codex can dispatch them in parallel.
All writes are **idempotent** (re-running updates the existing file) and **reversible** via `uninstall-mcp` (which only removes the `timps-swarm` key and the `timps-*.md` files — your other config is untouched).
---
## The killer commands
```bash
# Security audit — secrets + CVEs + SAST, no backend, no API key
npx timps-swarm audit ./
# Full 10-agent SDLC pipeline on any codebase
npx timps-swarm fix ./src --language python
# Generate a complete OpenAPI spec from plain English
npx timps-swarm api-design "billing API with metered usage and Stripe webhooks"
# Design a DB schema with DDL, ER diagram, and migrations
npx timps-swarm db-design "multi-tenant SaaS with usage-based billing"
# Diagnose your machine (12 specialist agents)
npx timps-swarm health
```
---
## MCP integrations
```bash
npx timps-swarm install-mcp # auto-detect and configure all installed tools
npx timps-swarm install-mcp --tool cursor # single tool only
npx timps-swarm install-mcp --dry-run # preview without writing files
```
| Tool | Config written |
|------|----------------|
| Claude Code | `~/.claude/mcp.json` |
| Cursor | `~/.cursor/mcp.json` |
| Windsurf | `~/.windsurf/mcp.json` |
| Continue | `~/.continue/config.json` |
| Zed | `~/.config/zed/settings.json` |
| Aider | `~/.aider.conf.yml` |
| Goose | `~/.config/goose/config.yaml` |
| Gemini CLI | `~/.gemini/settings.json` |
| Codex CLI | `~/.codex/config.json` |
| Amp | `~/.amp/mcp.json` |
| Warp | `~/.warp/mcp_servers.json` |
| VS Code / Cline / Copilot | `.vscode/mcp.json` (workspace) |
<details>
<summary>Manual config snippets (all tools)</summary>
`install-mcp` writes the snippet below into each IDE config. The `env:` block forwards whichever API keys you have set in your shell; it's optional (the IDE usually inherits env, but explicit is safer for sandboxed hosts).
**Claude Code** — `~/.claude/mcp.json`
```json
{
"mcpServers": {
"timps-swarm": {
"command": "npx",
"args": ["timps-swarm", "mcp"],
"env": {
"GEMINI_API_KEY": "...",
"ANTHROPIC_API_KEY": "..."
}
}
}
}
```
**Cursor / Windsurf / Gemini CLI / Codex CLI / Amp** — same format as above, different path.
**VS Code / Cline / Roo Code / GitHub Copilot** — `.vscode/mcp.json`
```json
{
"mcp": {
"servers": {
"timps-swarm": { "type": "stdio", "command": "npx", "args": ["timps-swarm", "mcp"] }
}
}
}
```
**Continue** — `~/.continue/config.json`
```json
{ "mcpServers": [{ "name": "timps-swarm", "command": "npx", "args": ["timps-swarm", "mcp"] }] }
```
**Aider** — `~/.aider.conf.yml`
```yaml
mcp-servers:
timps-swarm:
command: npx
args: [timps-swarm, mcp]
type: stdio
```
**Zed** — `~/.config/zed/settings.json`
```json
{
"assistant": {
"mcp_servers": {
"timps-swarm": { "command": "npx", "args": ["timps-swarm", "mcp"] }
}
}
}
```
**Goose** — `~/.config/goose/config.yaml`
```yaml
extensions:
- name: timps-swarm
type: stdio
cmd: npx timps-swarm mcp
enabled: true
```
**GitHub Actions** — reusable workflow
```yaml
jobs:
generate:
uses: Sandeeprdy1729/timps-swarm/.github/workflows/timps-swarm.yml@main
with:
task: "Build a microservice for JWT authentication"
language: python
secrets:
GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
```
</details>
---
## LLM providers
Tries providers in priority order, uses the first available one.
| Priority | Provider | Env var | Notes |
|----------|----------|---------|-------|
| 1 | MCP Sampler | *(auto)* | Uses the host tool's model |
| 2 | Gemini 2.5 Flash | `GEMINI_API_KEY` | Recommended — fast + generous free tier |
| 3 | Anthropic Claude | `ANTHROPIC_API_KEY` | Best for complex reasoning |
| 4 | OpenAI GPT-4o | `OPENAI_API_KEY` | |
| 5 | Groq Llama 3.3 70B | `GROQ_API_KEY` | Fastest API inference |
| 6 | Ollama | *(auto-detected)* | Fully offline, no API key |
| 7 | TIMPS-Coder 0.5B | *(built-in)* | Always available |
```bash
export GEMINI_API_KEY=... # free tier, fastest start
export ANTHROPIC_API_KEY=... # optional
```
---
<details>
<summary><strong>The 161 agents — full list</strong></summary>
The MCP server exposes **161 specialist agents** across 9 categories. Every one is also registered as a native Claude Code / Cursor / Codex sub-agent.
| Category | Count | Examples |
|----------|------:|----------|
| **Priority** | 68 | research_agent, ab_testing_agent, abdm_agent, agent_composer, browser_automation, churn_predictor, demand_forecaster, dependency_agent, digilocker_agent, dpdp_act_auditor, federated_learning, finetuning_agent, fssai_compliance_agent, gst_compliance, indiehacker_agent, model_evaluator, model_perf_monitor, podcast_show_notes_writer, prompt_injection_scanner, quantum_ready, rag_designer, rag_evaluator, red_team_agent, release_manager, sbom_generator, security_remediation, service_mesh_configurator, sprint_planning_agent, storybook_story_generator, threat_intel_analyst, upi_agent, vector_db_agent, voice_agent_designer, wearable_health_coach, web3_agent, win_loss_analyst, … |
| **Expert Diagnostics** | 51 | dependency_rebel, kubernetes_navigator, docker_compose_architect, pipeline_healer, compliance_auditor, incident_response_coordinator, accessibility_tester, mcp_server_generator, observability_cost_optimizer, license_compliance_scanner, container_image_scanner, adr_writer, contract_reviewer, court_case_summarizer, data_pipeline, db_migration_pilot, disaster_recovery, game_day_facilitator, git_workflow_automator, graphql_agent, iac_drift_detector, load_testing, local_rag_builder, log_pattern_analyzer, phishing_simulator, postmortem_agent, test_intelligence, visual_regression_detective, web_scraping, web_search, … |
| **Computer Health** | 12 | system_optimizer, file_organizer, environment_doctor, security_guard, network_medic, battery_analyst, update_manager, log_interpreter, privacy_cleaner, media_librarian, backup_sentinel, context_switcher |
| **Developer Workflow** | 12 | issue_triager, boilerplate_architect, pr_reviewer, dependency_sentinel, unit_test_writer, docstring_generator, log_detective, sql_optimizer, sprint_reporter, flaky_test_hunter, api_contract_auditor, content_multiplier |
| **Knowledge Worker** | 7 | inbox_gatekeeper, meeting_condenser, research_scout, trend_monitor, data_wrangler, competitor_tracker, agri_commodity_forecaster |
| **Meta** | 6 | list_agents, dispatch, full_checkup, list_providers, connect_tools, tool_status |
| **Context / Kernel** | 3 | context_briefing, delegate, kernel_status |
| **SDLC Pipeline** | 1 | run_task (the 10-node LangGraph orchestrator: PM → Architect → Code → Review → QA → Security → Perf → Docs → DevOps) |
```bash
# Trigger the full SDLC pipeline
python3 give_work.py "Build a rate-limited REST API for user authentication"
# PM → Architect → Code → Review → QA → Security → Perf → Docs → DevOps
# Run a computer health checkup
npx timps-swarm health
python3 give_work.py "My laptop fan is always running"
# Delegate a multi-step goal
npx timps-swarm delegate "fix the auth bug and ensure 80% test coverage"
# Call any of the 161 directly from the CLI
npx timps-swarm mcp # then use any MCP client
```
The **Self-Critic Agent** is the most valuable one — it scores any output 1–10 and re-runs the originating agent until the threshold is met, closing the quality loop across the entire swarm.
> The 161 includes Phase 3 (12 priority), Phase 5 (7 more), Phase 6 nextgen (21 — security/DevOps/MLOps/emerging), Phase 7 (32 — India verticals, compliance, content, sales/voice, research), and `timps_batch` for parallel delegation. The `src/tool_connectors` module has a separate `TOOLS` dict (24 IDE config shortcuts — `claude_code`, `cursor`, etc.) used at runtime by `timps_connect_tools` and `timps_tool_status`; those are not part of the 161.
</details>
---
## CLI
```bash
npm install -g timps-swarm # or: npx timps-swarm <command>
```
```
COMMANDS
audit <path> Security audit — secrets + CVEs + SAST (works offline)
fix <path> Run the full 10-agent SDLC pipeline
research <topic> Research a topic before writing code
api-design <desc> Generate an OpenAPI 3.1 spec from plain English
db-design <desc> Design a database schema with DDL + ER diagram
n8n <desc> Generate a complete n8n workflow JSON
refactor [path] Detect code smells + produce refactored version
test-data <schema> Generate realistic seed / fixture data
monitor <service> Prometheus + Grafana + alerting config
ui <desc> UI component spec + code + accessibility audit
cost <arch> Cloud cost estimate + savings recommendations
critique <content> Score output 1-10, auto-improve until threshold
health Computer health checkup (12 agents)
providers Show configured LLM providers
install-mcp Auto-configure TIMPS in 9 AI tools + 161 sub-agents
uninstall-mcp Remove the MCP config and 161 sub-agent .md files
start [--repo <path>] Start the TIMPS Swarm API server (port 8000)
mcp [--repo <path>] Start the MCP stdio server (Python or Node.js fallback)
FLAGS (install-mcp)
--tool <id> Only configure one IDE (claude-code, cursor, codex-cli, …)
--no-sub-agents Skip writing 161 sub-agent .md files (MCP config only)
--dry-run Preview without writing anything
--silent Suppress output (postinstall)
ENV VARS
TIMPS_API_URL API server URL (default http://localhost:8000)
Set to a remote URL to point every tool call at it.
TIMPS_REPO Explicit path to the Python repo for backend commands
GEMINI_API_KEY Free tier — fastest start
ANTHROPIC_API_KEY Optional
OPENAI_API_KEY Optional
GROQ_API_KEY Optional
OLLAMA_HOST Default http://localhost:11434
REDIS_URL Default redis://localhost:6379/0
```
If `timps-swarm mcp` is invoked but no Python repo is on disk, it transparently falls back to the bundled `cli/lib/mcp-proxy.js` — a Node.js JSON-RPC 2.0 stdio proxy that forwards every tool call to `${TIMPS_API_URL}/mcp/tools/call`. So `npm install -g timps-swarm` is enough to get a working MCP server, as long as a FastAPI server is reachable.
---
## Architecture
```
User / AI coding tool
(Claude Code, Cursor, Codex, …)
│
┌────────────────────────┼────────────────────────┐
│ stdio JSON-RPC 2.0 │ │
▼ ▼ ▼
┌──────────────────────┐ ┌──────────────────────┐ ┌────────────────────┐
│ mcp_server/server.py │ │ cli/lib/mcp-proxy.js │ │ src/main.py │
│ Python — 161 tools, │ │ Node.js fallback │ │ FastAPI + WS │
│ full MCP sampling │ │ (npm-only path) │ │ /swarm/run, │
│ │ │ │ │ /agents/*, │
│ │ │ │ │ /mcp/tools, │
│ │ │ │ │ /mcp/tools/call, │
│ │ │ │ │ /health, /ws │
└──────────┬───────────┘ └──────────┬───────────┘ └──────────┬─────────┘
│ │ │
│ TOOLS / dispatch │ POST /mcp/tools/call │
│ ◀───────────────────────┴──────────────────────────▶│
│ │
│ mcp_server/server._TOOL_HANDLERS │
│ (161 tools, in-process) │
└─────────────────────────┬───────────────────────────┘
│
Swarm Bridge
│
┌───────────────────┬──────────┴──────────┬───────────────────┐
▼ ▼ ▼ ▼
SDLC DAG Health Graph Specialist Agents Context / Kernel
(10 nodes) (12 nodes) (120 direct calls) (3 nodes)
│ │ │ │
└───────────────────┴─────────────────────┴───────────────────┘
│
LLM Router
┌─────────────┬─────────────────┼─────────────┬───────────────┐
▼ ▼ ▼ ▼ ▼
Gemini Anthropic OpenAI Groq Ollama
2.5 Flash Claude GPT-4o Llama 3.3 (local)
+ TIMPS-Coder 0.5B
```
Three transport paths converge on the same dispatch table:
1. **Python MCP stdio** (`mcp_server/server.py`) — full MCP sampling, in-process, 161 tools. Used when the Python repo is on disk.
2. **Node.js MCP stdio proxy** (`cli/lib/mcp-proxy.js`) — pure stdio JSON-RPC 2.0 that proxies `tools/list` + `tools/call` to a running FastAPI server. Used when only the npm package is installed (no Python repo).
3. **FastAPI REST + WebSocket** (`src/main.py`) — `/swarm/run`, `/agents/*`, `/health`, `/ws`, plus the bridge endpoints `/mcp/tools` (catalogue) and `/mcp/tools/call` (dispatch).
**Layer 1 — Computer Manager** (`src/layer1_computer_manager.py`) — isolated working directories, CPU/memory/disk caps per agent.
**Layer 2 — Swarm Bridge** (`src/layer2_swarm_bridge.py`) — agent lifecycle: spawning, team formation, LangGraph DAG execution, result collection.
**Layer 3 — CLI** (`src/layer3_swarm_cli.py`) — `give_work.py` and the npm CLI.
---
## REST API
```bash
curl http://localhost:8000/health
curl http://localhost:8000/health/full # deep check with provider status
curl -X POST http://localhost:8000/swarm/run \
-H "Content-Type: application/json" \
-d '{"request": "Fix SQL injection in my FastAPI endpoint", "language": "python"}'
curl -X POST http://localhost:8000/agents/refactor \
-d '{"code": "...", "language": "python", "goals": ["reduce_complexity"]}'
curl http://localhost:8000/providers
# MCP bridge (used by cli/lib/mcp-proxy.js)
curl http://localhost:8000/mcp/tools # full 161-tool catalogue
curl -X POST http://localhost:8000/mcp/tools/call \
-H "Content-Type: application/json" \
-d '{"name": "timps_list_agents", "arguments": {}}' # call any tool over HTTP
wscat -c ws://localhost:8000/ws # real-time stream
```
Full interactive docs at `http://localhost:8000/docs` when the server is running.
---
## Training custom adapters
The Code Generator uses TIMPS-Coder — a 0.5B model with 20 LoRA adapters, one per bug class. Add examples and push — GitHub Actions trains new adapters automatically.
```bash
cp my_bugs.jsonl datasets/custom/
git add datasets/custom/my_bugs.jsonl
git commit -m "feat: 40 new Python async bug examples"
git push origin main
```
Set `HF_TOKEN` and `HF_REPO_ID` in repo secrets. The pipeline merges your data, trains 20 adapters in parallel on Apple Silicon (MLX), benchmarks, and publishes to HuggingFace.
**The 20 bug-class adapters:** `java_npe` · `java_ioob` · `java_concurrent` · `python_keyerror` · `python_typeerror` · `python_recursion` · `python_async` · `python_logic` · `javascript_null` · `javascript_scope` · `javascript_async` · `cpp_memory` · `cpp_bounds` · `go_routine` · `rust_borrow` · `sql_injection` · `xss_vuln` · `auth_bypass` · `performance_slow` · `api_design`
---
## Hardware
| Setup | RAM | Notes |
|-------|-----|-------|
| Minimum | 8 GB | One Ollama model at a time |
| Recommended | 16 GB | All models loaded simultaneously |
| Fine-tuning | 8 GB Apple Silicon | MLX on M1/M2/M3/M4 |
---
## Security
API key auth is off by default. Enable when sharing across a team:
```bash
TIMPS_AUTH=1 make up-local
python3 give_work.py --keygen "sandeep-laptop" # generate key (shown once)
python3 give_work.py --revoke timps-sk-xxxx # revoke a key
```
Keys stored as SHA-256 hashes in `~/.timps/.secrets` (chmod 600).
---
## Contributing
PRs welcome against `main`. Conventional commits, please.
```bash
git clone https://github.com/Sandeeprdy1729/timps-swarm
cd timps-swarm && pip install -e ".[dev]"
make up-local # starts the FastAPI server on :8000
```
> `make test` is currently a no-op — `tests/` is empty. Existing runnable test scripts are top-level (`python3 mcp_server/test_server.py`, `python3 test_computer_allocation.py`). Add a `tests/` directory and wire it into `pyproject.toml` before relying on pytest.
Lint: `ruff check .` (configured in `pyproject.toml`, no `make lint` target). Typecheck: none configured. Python ≥ 3.10, CI pins 3.11.
---
<div align="center">
Built on [TIMPS-Coder](https://github.com/Sandeeprdy1729/timps-coder) — a 0.5B model fine-tuned with 20 LoRA adapters for specific bug patterns.
MIT License · [Discord](https://discord.gg/MmsTNm8WF6) · [npm](https://www.npmjs.com/package/timps-swarm)
</div>