nautilus-trader MCP server
Provides LLMs with code and documentation search over nautilus_trader via LSP-based symbol lookup and semantic embedding-based doc retrieval.
README
nautilus-trader MCP server
What this is
An MCP (Model Context Protocol) server that gives an LLM (Claude Code, Codex CLI, etc.) two ways to look things up in nautilus_trader while writing strategy code against it:
- Code search (
index.py) -- structural search over the actual source (Python + Rust), by symbol name. Not fuzzy-text/embedding search: it finds the real class/function/struct and returns its docstring or full source. - Doc search (
rags/) -- semantic (embedding-based) search over the project's markdown docs (concepts, guides, tutorials), for "how do I..." questions that don't map to a single symbol name.
How it works
index.pyspawns two real language servers as subprocesses and talks LSP (JSON-RPC over stdio) to them directly --pylspfor the Python source undernautilus_trader/python/nautilus_trader,rust-analyzerfor the Rust source undernautilus_trader/crates.documentSymbolfinds top-level classes/functions/structs/impls;hovergets the docstring (Python only -- see Known limitations). Results are cached to.code_index_cache.jsonsince building it costs ~25s (mostly rust-analyzer over ~2600 files).rags/rag_build.pychunks every file underdocs/and builds adspy.retrievers.Embeddingsindex (Gemini embeddings), saved torags/(config.json+corpus_embeddings.npy) plus ashape.jsonthat records the original folder structure sorags/search.pycan filter to a subfolder.mcp_server.pywires both into 5 MCP tools:search_code,get_code_doc,get_code_source,search_docs,show_doc_keys.
Setup
git clone https://github.com/GwangPyo/NautilusTraderMCP.git
cd NautilusTraderMCP
cp .env.example .env # fill in GEMINI_API_KEY (and OPENAI/ANTHROPIC if you use load_model)
./install.sh # conda env "mcp" + deps, nautilus_trader clone, code index, doc index
install.sh is idempotent: re-running it skips the nautilus_trader clone, the
docs/ copy, and the (paid) doc-embedding build if they already exist. Set
ENV_NAME=<name> to use a different conda env name (used for testing so it
doesn't touch the real mcp env).
An env manager isn't required -- uv venv && uv pip install -e . works too;
install.sh just standardizes on conda for a reproducible one-command setup.
Register with a client
./add_claude.sh # claude mcp add
./add_codex.sh # codex mcp add
Both just point the client at <conda mcp env>/bin/python3 mcp_server.py over stdio.
Known limitations / TODO
- [ ]
.code_index_cache.jsonandrags/{config.json,corpus_embeddings.npy,shape.json}have no invalidation -- ifnautilus_trader/ordocs/change, you have to delete the cache files by hand and re-run to pick it up. - [ ] No automated tests -- everything so far has been verified by hand (fresh conda env, fresh uv env, real MCP client over stdio).
- [ ]
nautilus_trader/is cloned frommain(unpinned) -- can drift over time; nothing currently checks it against a known-good commit/tag.
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