dedalus-python-server-example

windsornguyen/dedalus-python-server-example

3.2

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Dedalus MCP Documentation Server is an AI-powered server designed to serve and query documentation efficiently, with capabilities for AI-driven Q&A and document analysis.

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Dedalus MCP Documentation Server

An MCP server for serving and querying documentation with AI capabilities. Built for the YC Agents Hackathon.

Quick Start (Local Development)

# Install uv package manager (same as Dedalus uses)
brew install uv  # or pip install uv

# Install dependencies
uv sync --no-dev

# Configure API keys for AI features
cp config/.env.example .env.local
# Edit .env.local and add your OpenAI API key

# Test
uv run python tests/test_server.py

# Run
uv run main

Deploy to Dedalus

What Dedalus Needs

  • pyproject.toml - Package configuration with dependencies
  • main.py (root) - Entry point that Dedalus expects
  • src/main.py - The actual MCP server code
  • docs/ - Your documentation files

Deployment Steps

  1. Set Environment Variables in Dedalus UI:

    • OPENAI_API_KEY - Your OpenAI API key (required for AI features)

  2. Deploy:

dedalus deploy . --name "your-docs-server"

How Dedalus Runs Your Server

  1. Installs dependencies using uv sync from pyproject.toml
  2. Runs uv run main to start the server
  3. Server runs in /app directory in container
  4. Docs are served from /app/docs

Features

  • Serve markdown documentation
  • Search across docs
  • AI-powered Q&A (with OpenAI)
  • Rate limiting (10 requests/minute) to protect API keys
  • Ready for agent handoffs

Tools Available

  • list_docs() - List documentation files
  • search_docs() - Search with keywords
  • ask_docs() - AI answers from docs
  • index_docs() - Index documents
  • analyze_docs() - Analyze for tasks

Documentation

See docs/ directory for:

License

MIT