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.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.