tc-help-mcp

A remote MCP server that gives the team's Claude.ai workspace live, always-current access to product documentation across the portfolio — TutorCruncher and Bobbin — with room to add more products by config alone.

It is a general product-docs assistant: the team adds it once as a remote connector and asks questions; Claude calls the tools, the server fetches from source on demand, and Claude reasons over the returned content. There is no local index and no persisted copy of the docs — the docs are the only source of truth, so answers never drift. A short in-memory TTL cache (default 300s) exists purely for latency/rate-limit protection.

Sources at launch:

1. TutorCruncher help docs — Intercom help centre, via the Intercom Articles API.

2. Bobbin help docs — Intercom help centre (separate Intercom workspace → separate token).

3. TutorCruncher API docs — the public tutorcruncher/tc-api-docs repo.

Tools

Help tools take an optional product filter ("tutorcruncher" | "bobbin"); unset spans all configured products. Every result carries its product so answers stay correctly attributed.

Related MCP server: DevDocs MCP Server

tc-api-docs structure (Outcome B)

pages/api.yml is an index (info_sections + endpoint_sections), each entry pointing to a layout file (e.g. pages/clients/clients.yml). A layout's sections: list references separate content files per subsection: description (.md), attributes/filters (.yml), response (.json), and code (.py) plus code_type/code_url. Paths are repo-absolute under pages/. get_api_section resolves a section, fetches its layout, fans out over the referenced files (cached, concurrency-capped) and assembles one clean markdown document.

Configuration

All configuration is via environment variables (see .env.example). Never commit values. Each Intercom workspace has its own token — one token does not span both products.

Adding another product

A product is one line in KNOWN_HELP_PRODUCTS in app/config.py ((product, help_centre_base)) plus an INTERCOM_TOKEN_<PRODUCT> env var. Products whose token is unset are skipped. No tool changes are needed.

Local development

make install-dev          # deps + pre-commit hooks
cp .env.example .env       # fill in tokens; set ALLOW_UNGATED=1 for local use
make lint                  # ruff + ty
make test                  # pytest -n auto
make run-dev               # serve on 0.0.0.0:$PORT

Deployment

Built as a single-stage Docker image and released to Heroku (container stack) by .github/workflows/deploy.yml on push to main. Set secrets via Heroku config, never the repo:

Deploys run via .github/workflows/deploy.yml (GitHub Actions builds the image and releases it to the container-stack Heroku app help-mcp on push to main). The repo needs a HEROKU_API_KEY secret; the Heroku app needs its config vars set:

heroku stack:set container -a help-mcp
heroku config:set -a help-mcp \
  GITHUB_OAUTH_CLIENT_ID=... GITHUB_OAUTH_CLIENT_SECRET=... \
  BASE_URL=https://help-mcp-5710e51f90a5.herokuapp.com \
  JWT_SIGNING_KEY="$(openssl rand -hex 32)" \
  ALLOWED_GITHUB_ORG=tutorcruncher \
  INTERCOM_TOKEN_TUTORCRUNCHER=... INTERCOM_TOKEN_BOBBIN=...

Then register https://help-mcp-5710e51f90a5.herokuapp.com/mcp as a remote connector in the team's Claude.ai workspace.