Content
[](https://github.com/TheFractalyst/QuantConnectMCP)
[](https://pypi.org/project/qc-lean-mcp/)
[](https://python.org/)
[](https://trychroma.com/)
[](https://modelcontextprotocol.io/)
[](LICENSE)
[](https://github.com/TheFractalyst/QuantConnectMCP/actions/workflows/ci.yml)
Complete QuantConnect/Lean reference documentation MCP server with 1265 entries
covering 100% of the official QuantConnect v2 documentation sitemap.
[Quick Start](#quick-start) |
[Tools](#tools) |
[Configuration](#configuration) |
[Database](#database) |
[Development](#development)
---
## One Command. Two Minutes. Fully Functional.
```bash
pip install qc-lean-mcp
qc-lean-mcp
```
That's it. On first run, the server auto-builds the ChromaDB vector store from
shipped JSON data (takes 30-60 seconds for embedding model download + indexing).
Subsequent runs start instantly.
**What you get:**
- 6 MCP tools for QuantConnect/Lean docs lookup, code validation, and template generation
- 1265 entries indexed in a local ChromaDB vector store (100% offline)
- Sub-millisecond hot cache for priority lookups
- Python AST validation for Lean algorithms
- Common Python.NET issue detection and auto-repair
- Works with Claude Desktop, Cursor, Windsurf, OpenCode, and any MCP client
**What you need:**
- Python 3.10+
- Any MCP-compatible AI client
---
## Why QuantConnectMCP?
AI coding assistants hallucinate Lean API syntax. The QuantConnect API is large
(QCAlgorithm, Algorithm Framework, 200+ indicators, multiple asset classes) and
constantly evolving. Models trained on older code get method signatures wrong.
QuantConnectMCP gives AI assistants **authoritative, real-time access** to the
complete QuantConnect/Lean reference:
- **100% coverage**: 1257/1257 official QuantConnect v2 docs sitemap URLs
- **Semantic search**: Vector embeddings find relevant docs by meaning, not keywords
- **Code validation**: `qc_validate` checks Python Lean algorithms for common mistakes
- **Auto-repair**: `qc_repair` fixes Python.NET bridge issues, missing self. prefix, etc.
- **Code generation**: `qc_scaffold` generates validated algorithm templates
- **100% local**: No network calls at runtime (ChromaDB auto-builds from shipped data)
---
## Tools
```
+---------------------------+----------------------------------------------+
| Tool | Description |
+---------------------------+----------------------------------------------+
| qc_lookup(name, kind?) | Get complete docs for a symbol by exact name |
| qc_search(query, ...) | Semantic search across all docs |
| qc_browse(namespace, ...) | Enumerate all members of a namespace |
| qc_validate(code?, ...) | Validate Python syntax for Lean algorithms |
| qc_repair(code, context) | Fix common Python.NET issues in Lean code |
| qc_scaffold(kind, name) | Generate algorithm/indicator/research template|
+---------------------------+----------------------------------------------+
```
---
## Quick Start
### Claude Desktop
Add to `~/Library/Application Support/Claude/claude_desktop_config.json`:
```json
{
"mcpServers": {
"qc-lean-mcp": {
"command": "qc-lean-mcp"
}
}
}
```
### Cursor / Windsurf / OpenCode
```json
{
"mcpServers": {
"qc-lean-mcp": {
"command": "qc-lean-mcp"
}
}
}
```
### SSE (HTTP)
```bash
qc-lean-mcp
# Then connect to http://localhost:8080
```
Or with environment variables:
```bash
TRANSPORT=sse PORT=8080 qc-lean-mcp
```
---
## Configuration
```
+-------------------------+---------------+--------------------------------+
| Env Var | Default | Description |
+-------------------------+---------------+--------------------------------+
| TRANSPORT | stdio | Transport: stdio or sse |
| PORT | 8080 | Port for SSE transport |
| QC_DB_PATH | ./qc_db | ChromaDB path |
| QC_COLLECTION | qc_reference | ChromaDB collection name |
| QC_EMBED_MODEL | all-MiniLM-L6 | Sentence transformer model |
| QC_MAX_RESULTS | 100 | Max search results |
| LOG_LEVEL | INFO | Logging level |
| LAZY_MODEL | 0 | Skip model preload at startup |
+-------------------------+---------------+--------------------------------+
```
---
## Database
- 1265 entries (QuantConnect v2 docs)
- 1257/1257 sitemap URLs (100% coverage)
- 20 namespaces: cloud, indicators, writing-algorithms, cli, docs, datasets,
research, securities, reality-modeling, local, engine, ai, framework, etc.
- Hot cache for sub-millisecond priority lookups
- Auto-built on first run from shipped JSON data (14MB)
To rebuild the database:
```bash
qc-lean-mcp build
```
---
## Development
```
git clone https://github.com/TheFractalyst/QuantConnectMCP.git
cd QuantConnectMCP
pip install -e ".[dev]"
pytest tests/ -v
```
### Re-index ChromaDB
```bash
python pipeline/merge_and_index.py --reset
```
## Docker
```bash
docker build -t qc-lean-mcp .
docker run -p 8080:8080 -e TRANSPORT=sse qc-lean-mcp
```
## Tech Stack
- **FastMCP 3.0** - MCP server framework with FileSystemProvider auto-discovery
- **ChromaDB** - Local vector database for semantic search (cosine, 384-dim)
- **SentenceTransformers** - `all-MiniLM-L6-v2` embedding model
- **RapidFuzz** - Fuzzy string matching for name lookups
- **Loguru** - Structured logging
## Links
- [fractalyst.dev](https://fractalyst.dev/) - Portfolio
- [QuantConnect Documentation](https://www.quantconnect.com/docs/v2/) - Official docs
- [LEAN Engine](https://www.quantconnect.com/lean) - Open-source algorithmic engine
- [@TheFractalyst](https://x.com/TheFractalyst) - X / Twitter
## License
MIT - see [LICENSE](LICENSE)
