Alliance Documentation MCP Server

A Model Context Protocol (MCP) server that provides programmatic access to the Digital Research Alliance of Canada's technical documentation. This server mirrors the documentation from the MediaWiki site and exposes it through MCP resources and tools for use with MCP-compatible clients.

Features

• Documentation Mirroring: Syncs documentation from the Alliance MediaWiki site
• MCP Resources: Exposes individual documentation pages as MCP resources
• Full-Text Search: Whoosh-backed content and title search with highlights and scoring
• Related Pages: Embeddings-backed related-page discovery with heuristic fallback
• Search & Query Tools: Provides search, categorization, and querying capabilities
• Startup Refresh: Container entrypoint triggers an incremental sync on boot; schedule additional runs as needed
• Markdown Storage: Stores documentation as markdown files with metadata

Quick Start

Prerequisites

• Python 3.11+
• uv for package management

Installation

1. Clone and setup the repository:

   git clone <repository-url>
   cd alliance-docs-mcp

2. Install dependencies:

   uv sync

3. Configure environment (optional): Create a .env file (or export the variables directly) if you want to override defaults. For example:

   MEDIAWIKI_API_URL=https://docs.alliancecan.ca/mediawiki/api.php
   DOCS_DIR=./docs
   USER_AGENT=AllianceDocsMCP/1.0

4. Initial documentation sync:

   uv run python scripts/sync_docs.py

   Note: Docker images built from this repository automatically run this full sync during the image build so containers start with a warm cache.

5. Start the MCP server:

   uv run python -m alliance_docs_mcp.server

Usage

MCP Resources

The server exposes documentation pages as MCP resources:

• Resource URI: alliance-docs://page/{slug}
• Content: Markdown content of the documentation page

Example:

alliance-docs://page/technical_documentation

MCP Tools

The server provides several tools for querying documentation:

search_docs(query: str, category: Optional[str] = None, limit: int = 20, search_content: bool = True, fuzzy: bool = False)

Search documentation pages by title (fallback) or full-text index when available. Full-text results include relevance scores and highlighted snippets.

Parameters:

• query: Search query string
• category: Optional category filter
• limit: Maximum number of results
• search_content: Use full-text index when available (default: True)
• fuzzy: Enable fuzzy matching for typo tolerance (full-text only)

Returns: List of matching pages with metadata, highlights, and scores (when indexed)

list_categories()

List all available documentation categories.

Returns: List of category names

get_page_by_title(title: str)

Find a specific page by its title.

Parameters:

• title: Page title to search for

Returns: Page metadata or None if not found

list_recent_updates(limit: int = 10)

List recently updated pages.

Parameters:

• limit: Maximum number of pages to return

Returns: List of recent pages with metadata

get_page_info(slug: str)

Get detailed information about a specific page.

Parameters:

• slug: Page slug

Returns: Detailed page information including metadata

list_all_pages()

List all available documentation pages.

Returns: List of all pages with basic metadata

find_related_pages(slug: str, limit: int = 5)

Embeddings-backed related-pages helper (Chroma + sentence-transformers) with automatic fallback to lightweight heuristics.

Parameters:

• slug: Source page slug
• limit: Max related pages to return
• min_score: Optional similarity threshold when embeddings are available

Returns: List of related pages with similarity scores (or heuristic scores when falling back)

MCP Prompts

The server provides reusable prompt templates that guide LLMs on how to effectively query and use the documentation system. These prompts can be used by MCP clients to structure queries and improve consistency.

documentation_search_guide(query: str, category: Optional[str] = None)

Guide for effectively searching Alliance documentation. Provides instructions on using the search_docs tool, interpreting search results, and filtering by category.

Parameters:

• query: The user's search query
• category: Optional category filter

Use Case: When an LLM needs to help a user search for documentation on a specific topic.

technical_question_template(question: str, context: Optional[str] = None)

Template for answering technical questions using documentation. Guides the LLM through searching, reading relevant pages, finding related content, and synthesizing information.

Parameters:

• question: The technical question to answer
• context: Additional context about what the user is trying to accomplish

Use Case: When an LLM needs to answer technical questions based on the documentation.

category_exploration_guide(category: str, purpose: Optional[str] = None)

Guide for exploring documentation by category. Helps discover pages within a specific category and understand the documentation structure.

Parameters:

• category: The category to explore
• purpose: What the user is trying to accomplish

Use Case: When an LLM needs to help users explore documentation in a specific category (e.g., "Getting Started", "Technical Reference").

related_content_discovery(topic: str, goal: Optional[str] = None)

Guide for finding related documentation pages. Provides instructions on using the find_related_pages tool and interpreting similarity scores.

Parameters:

• topic: The topic or page slug to find related content for
• goal: The user's goal (learning, troubleshooting, etc.)

Use Case: When an LLM needs to help users discover related documentation after finding a relevant page.

getting_started_helper(use_case: str)

Template for helping new users get started. Guides LLMs to point users to getting started documentation and common first steps.

Parameters:

• use_case: What the user wants to do (e.g., "set up account", "run first job", "install software")

Use Case: When an LLM needs to help new users with onboarding and initial setup tasks.

Synchronization

Manual Sync

Run a full synchronization (with rich progress bars and visual feedback):

uv run python scripts/sync_docs.py

Run an incremental sync (only changed pages):

uv run python scripts/sync_docs.py --incremental

Index controls:

uv run python scripts/sync_docs.py --rebuild-index       # Rebuild Whoosh index
uv run python scripts/sync_docs.py --no-index            # Skip indexing
uv run python scripts/sync_docs.py --index-dir /tmp/idx  # Custom index location
uv run python scripts/sync_docs.py --rebuild-related-index     # Rebuild related-page embeddings
uv run python scripts/sync_docs.py --no-related-index          # Skip related-page embeddings
uv run python scripts/sync_docs.py --related-index-dir /tmp/rel# Custom related index location
uv run python scripts/sync_docs.py --related-model-name all-MiniLM-L6-v2

The related-page index downloads the configured sentence-transformer model (default: all-MiniLM-L6-v2, ~90 MB) the first time it runs.

For FastMCP Cloud deployments, run one of the sync commands above locally and commit the updated docs/ directory before pushing so the hosted server always mirrors the latest content.

The sync script provides:

• Colored output with rich formatting
• Progress bars for download and processing phases
• Real-time statistics including pages/second
• Summary table with detailed metrics
• Error tracking with warnings for failed pages

Note: Markdown pages larger than 10 MB are stored as .md.gz files. The server automatically decompresses them at runtime, so no additional configuration is required.

LLM-Optimized Documentation Files

The sync process automatically generates two files for LLM consumption:

• docs/llms.txt: A simple directory listing all page names, categories, and URLs (~35 KB)
• docs/llms_full.txt.gz: Complete documentation content in a single compressed file (~2.6 MB compressed, ~393 MB uncompressed)

These files are regenerated on every sync (both full and incremental) and committed to the repository, making it easy for LLMs to access the entire documentation corpus.

Automated Sync

Set up a cron job for weekly updates:

# Add to crontab (runs every Sunday at 2 AM)
0 2 * * 0 cd /path/to/alliance-docs-mcp && uv run python scripts/sync_docs.py --incremental

This repository also ships with .github/workflows/weekly-sync.yml, which performs the same incremental sync on Sundays using GitHub Actions and pushes any changes back to main.

Configuration

Environment Variables

Set the following environment variables (via .env, shell exports, or your hosting platform's secret manager) to customize behavior:

• MEDIAWIKI_API_URL (default https://docs.alliancecan.ca/mediawiki/api.php)
• DOCS_DIR (default ./docs, or /data/docs in the container)
• USER_AGENT (default AllianceDocsMCP/1.0)
• SEARCH_INDEX_DIR (optional; overrides default DOCS_DIR/search_index)
• DISABLE_SEARCH_INDEX (set to 1/true/yes to force title-only fallback)
• RELATED_INDEX_DIR (optional; overrides default DOCS_DIR/related_index)
• RELATED_MODEL_NAME (sentence-transformer model, default all-MiniLM-L6-v2)
• RELATED_BACKEND (default chroma)
• DISABLE_RELATED_INDEX (set to 1/true/yes to skip related-page embeddings)

Server Configuration

The MCP server can be configured with command-line arguments:

uv run python -m alliance_docs_mcp.server --help

Options:

• --host: Host to bind to (default: localhost)
• --port: Port to bind to (default: 8000)
• --docs-dir: Documentation directory (default: ./docs)

Docker Deployment

The provided Docker image ships with a pre-synced documentation cache baked into /app/docs_seed. When the container starts, the entrypoint primes the configured DOCS_DIR from this seed (if empty) and then launches the MediaWiki sync in the background so the MCP server begins accepting connections immediately. You can configure startup behavior with:

• RUN_SYNC_ON_START=0 to skip the background sync (useful when running in read-only environments)
• SYNC_MODE=full to force a full resync instead of the default incremental sync
• The container starts the server via fastmcp run server_entrypoint.py:mcp --transport http --path /mcp/ --port 8080, so any additional FastMCP CLI flags can be injected by overriding CMD in your own image if needed.
• A lightweight /health endpoint is exposed for platform probes; point load balancer checks there instead of MCP protocol paths.

Project Structure

alliance-docs-mcp/
├── src/
│   └── alliance_docs_mcp/
│       ├── __init__.py
│       ├── server.py        # FastMCP server implementation
│       ├── mirror.py        # MediaWiki API client
│       ├── converter.py     # WikiText to Markdown converter
│       └── storage.py       # File storage and retrieval
├── docs/                    # Mirrored markdown files
│   ├── pages/               # Organized by category
│   └── index.json           # Page metadata index
├── scripts/
│   └── sync_docs.py         # Synchronization script
├── tests/                   # Test files
├── pyproject.toml           # Project configuration
└── README.md

Development

Running Tests

uv run pytest

Code Formatting

uv run black src/
uv run ruff check src/

Deployment Options

FastMCP Cloud (managed)

• Sign in at fastmcp.cloud with your GitHub account and create a project that points at this repository.
• Use server_entrypoint.py:mcp as the entrypoint so the platform runs the exported FastMCP server instance.
• Configure environment variables (e.g., MEDIAWIKI_API_URL, DOCS_DIR, USER_AGENT) via the project settings; the service installs dependencies directly from pyproject.toml.
• Push to main to trigger deployments; each pull request automatically gets its own preview environment for testing changes.

Self-managed container/VM

• Build the Docker image in this repo and run it anywhere that can expose HTTP on port 8080.
• Provide the same environment variables via your scheduler or container runtime.
• Point load balancer health checks at /health and connect MCP clients to the /mcp/ path served by fastmcp run.

Adding New Features

1. New MCP Tools: Add new tool functions to server.py
2. Storage Enhancements: Extend storage.py for new functionality
3. API Improvements: Modify mirror.py for different API interactions

Troubleshooting

Common Issues

1. Sync Failures: Check API access and network connectivity
2. Missing Pages: Verify MediaWiki API responses
3. Conversion Errors: Ensure beautifulsoup4/wikitextparser are installed and valid HTML is being stripped (use --no-strip-html to disable)

Logs

Check the sync.log file for synchronization issues:

tail -f sync.log

Debug Mode

Run with verbose logging:

uv run python scripts/sync_docs.py --verbose

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Digital Research Alliance of Canada for providing the documentation
• FastMCP for the MCP server framework
• uv for Python package management