LaserData Docs MCP

MCP server for answering questions from the LaserData documentation.

It serves two corpora, so an AI assistant answers Laser SDK and LaserData Cloud questions from the current docs rather than from training data:

• the guides: every page of docs.laserdata.com, read from the site's own llms-full.txt and keyed by site path (laser-sdk/memory, networking/private-link).

• the Python API: the public surface of the laser_sdk package, read from the laser_sdk.pyi type stub in laserdata/laser-sdk and keyed under python/laser_sdk/.

The guides say how Laser SDK is meant to be used and the API says what is callable, so every result says which corpus it came from.

Search is chunked BM25 with a small vocabulary bridge, and code blocks are first-class content. Related pages are found through the links between pages as well as shared terms.

Adapted from IggyDocMCP, the same server for the Apache Iggy docs.

Corpus sources

The guides are fetched from docs.laserdata.com and cached on disk for seven days. Set LASER_DOCS_FILE to a local copy of llms-full.txt to read that instead, fresh on every call.

The Python stub is a copy in pystub/laser_sdk.pyi, taken from laserdata/laser-sdk at 2a278e76e. Set LASER_PYTHON_STUB to its path. To update it:

curl -sL https://raw.githubusercontent.com/laserdata/laser-sdk/main/foreign/python/laser_sdk.pyi -o pystub/laser_sdk.pyi

Related MCP server: RAG Documentation MCP Server

Install

python3 -m venv .venv
. .venv/bin/activate
pip install -e .

Run

LASER_PYTHON_STUB=pystub/laser_sdk.pyi laser-doc-mcp

This serves over stdio. Set LASER_DOC_MCP_TRANSPORT=streamable-http and PORT to serve over HTTP, as the Docker image does.

Test

pip install -e ".[dev]"
make check

Use the hosted server

The hosted server is at https://laserdata-docs-mcp.fly.dev/mcp, with no sign-in. In Claude Code:

claude mcp add --transport http laserdata-docs https://laserdata-docs-mcp.fly.dev/mcp

Deploy

The image ships the Python stub and fetches the guides at runtime.

fly deploy

Pushes to main also deploy through .github/workflows/fly-deploy.yml, which needs a FLY_API_TOKEN repository secret.

For the OpenAI plugin directory, the server answers the domain-verification challenge at /.well-known/openai-apps-challenge with the token in the OPENAI_APPS_CHALLENGE secret, and returns 404 when it is unset:

fly secrets set OPENAI_APPS_CHALLENGE=<token from the portal>

Tools

• list_docs: every page, organised by section, with word counts and corpus; source restricts to website or python-api.

• get_doc: full text of one page by key (e.g. laser-sdk/quickstart, python/laser_sdk/Laser); unambiguous partial keys resolve automatically.

• search_docs: ranked search across both corpora, returning excerpts with their code blocks, each labelled Guide or Python API.

• find_examples: code examples by topic and language (Python, TypeScript, Rust, shell).

• extract_code_snippets: an inventory of code blocks, filtered by language or doc key.

• get_related_docs: pages related to one key, through links, backlinks, shared section and shared terms.

• explain_doc_map: the documentation sections and where to start for a new user, SDK developer, operator or AI assistant.

• refresh_docs: re-fetch the guides, bypassing the cache, and re-read the Python stub. Local stdio use only; the hosted server leaves it out, and its cache refills on each cold start.

Every tool is read-only, and is annotated readOnlyHint: true, destructiveHint: false and openWorldHint: false (refresh_docs is open-world, since it fetches).

Example questions

• How do I connect to Laser Stack from Python?

• How do I give an agent memory that survives a restart?

• What does Laser.connect accept?

• How do I set up PrivateLink for a deployment?

• Show me a TypeScript example that stores a key-value pair.

Licence

Apache License 2.0. See LICENSE.

Apache Iggy is a trademark of the Apache Software Foundation.