Advocu MCP Server

Advocu MCP Server

Enables Google Developer Experts, Docker Captains, and Microsoft MVPs to submit professional activity reports via conversational AI, with support for multiple programs and rate-limited API access.

Category
Visit Server

README

Advocu MCP Server

A unified Model Context Protocol (MCP) server that enables Google Developer Experts (GDEs), Docker Captains, and Microsoft MVPs to report their professional activities through conversational AI interfaces.

Built with FastMCP for seamless integration with Claude, Gemini, and other AI agents.

Features

  • šŸŽÆ Multi-Program Support: Single server for GDE, Docker Captains, and MVP programs
  • šŸš€ FastMCP-Powered: Simple, Pythonic MCP server with automatic schema generation
  • šŸ”’ Rate Limiting: Built-in rate limiting (30 req/min) to respect API limits
  • āœ… Type-Safe: Pydantic models for robust data validation
  • šŸ¤– Conversational: Natural language activity submission via AI agents
  • šŸ“Š Activity Management: Submit, list, and track activities across programs

āš ļø Important: Draft-Only Workflow

The Advocu API only allows creating DRAFTS via API. After creating an activity through the MCP server, you need to:

  1. āœ… Create draft via MCP/Claude (automated)
  2. 🌐 Go to the portal (manual step)
    • Docker Captains: https://hub.docker.com/
    • GDE: https://developers.google.com/community/experts
  3. šŸ“ Review the draft (verify data is correct)
  4. āœ… Click "Submit" to publish (manual step)

This is a limitation of the Advocu API, not the MCP server. All activities will be created as drafts that require manual publishing.

Supported Activities

Docker Captains

  • šŸŽ¤ Public speaking (conferences, meetups)
  • šŸ“ Resources (articles, videos, tutorials)
  • šŸŽ“ Events (workshops, hackathons)
  • šŸ’¬ Feedback sessions
  • šŸ“¢ Amplification (social media, community)

Google Developer Experts (GDE)

  • šŸŽ¤ Public speaking
  • šŸ“ Content creation
  • šŸŽ“ Workshops
  • šŸ‘Øā€šŸ« Mentoring
  • šŸ” Product feedback
  • šŸ¤ Googler interactions
  • šŸ“– Success stories

Microsoft MVPs

(Coming soon - different API endpoint)

Quick Start

1. Prerequisites

  • Python 3.10 or higher
  • Access token from your program (GDE and/or Docker Captains)

2. Installation

# Clone the repository
git clone https://github.com/yourusername/advocu-mcp-server.git
cd advocu-mcp-server

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -e .

3. Configuration

Create a .env file with your tokens:

cp .env.example .env

Edit .env and add your tokens:

# For GDEs
GDE_ACCESS_TOKEN=your_gde_token_here

# For Docker Captains
DOCKER_ACCESS_TOKEN=your_docker_token_here

How to Get Your Token

For Google Developer Experts:

  1. Visit https://devlibrary.advocu.com/
  2. Go to Settings → Integrations → API
  3. Click "Generate your token"
  4. Copy the token

For Docker Captains:

  1. Visit the Docker Captains portal
  2. Go to Settings → Integrations → API
  3. Click "Generate your token"
  4. Copy the token

4a. Configure Claude Desktop (Optional)

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on Mac):

{
  "mcpServers": {
    "advocu": {
      "command": "python",
      "args": ["-m", "src.server"],
      "cwd": "/path/to/advocu-mcp-server",
      "env": {
        "PYTHONPATH": "/path/to/advocu-mcp-server"
      }
    }
  }
}

4b. Configure Claude Code CLI (Recommended)

The project already includes a .mcp.json file for Claude Code CLI. Just verify it's configured:

# Check server status
claude mcp list

# You should see:
# advocu: .../venv/bin/python -m src.server - āœ“ Connected

If you need to reconfigure, edit .mcp.json:

{
  "mcpServers": {
    "advocu": {
      "type": "stdio",
      "command": "/home/falcon/advocu-mcp-server/venv/bin/python",
      "args": ["-m", "src.server"],
      "cwd": "/home/falcon/advocu-mcp-server",
      "env": {
        "PYTHONPATH": "/home/falcon/advocu-mcp-server"
      }
    }
  }
}

Note: Update the paths to match your installation directory.

5. Usage

Start chatting naturally with Claude (Desktop or CLI):

Examples:

"I gave a talk about Docker networking at KubeCon on June 5th, 2026 with 500 attendees"

"I published a tutorial on Cloud Run yesterday with 3000 views"

"I organized a workshop on Kubernetes last week with 30 people for 4 hours"

Claude will automatically use the appropriate MCP tools to submit your activities.

Available Tools

Docker Captains Tools

  • submit_docker_public_speaking - Submit speaking engagements
  • submit_docker_resource - Submit articles, videos, tutorials
  • submit_docker_event - Submit organized events
  • submit_docker_feedback - Submit feedback sessions
  • submit_docker_amplification - Submit social media amplification

GDE Tools

  • submit_gde_public_speaking - Submit speaking engagements
  • submit_gde_content - Submit content creation
  • submit_gde_workshop - Submit workshops
  • submit_gde_mentoring - Submit mentoring sessions
  • submit_gde_product_feedback - Submit product feedback
  • submit_gde_googler_interaction - Submit Googler interactions
  • submit_gde_story - Submit success stories

Utility Tools

  • list_recent_activities - List recent activities

Development

Project Structure

advocu-mcp-server/
ā”œā”€ā”€ src/
│   ā”œā”€ā”€ __init__.py
│   ā”œā”€ā”€ server.py              # Main FastMCP server
│   ā”œā”€ā”€ config.py              # Configuration management
│   ā”œā”€ā”€ clients/
│   │   ā”œā”€ā”€ __init__.py
│   │   └── advocu.py          # Advocu API client
│   ā”œā”€ā”€ models/
│   │   ā”œā”€ā”€ __init__.py
│   │   ā”œā”€ā”€ base.py            # Base models
│   │   ā”œā”€ā”€ docker.py          # Docker Captains models
│   │   └── gde.py             # GDE models
│   └── utils/
│       ā”œā”€ā”€ __init__.py
│       └── rate_limiter.py    # Rate limiting
ā”œā”€ā”€ tests/                      # Tests (coming soon)
ā”œā”€ā”€ pyproject.toml             # Project metadata
ā”œā”€ā”€ .env.example               # Environment template
└── README.md                  # This file

Running Tests

pytest

Code Quality

# Format code
ruff format .

# Lint code
ruff check .

API Reference

Advocu API

Base URLs:

  • GDE: https://api.advocu.com/personal-api/v1/gde
  • Docker Captains: https://api.advocu.com/personal-api/v1/dockercaptains

Authentication:

Authorization: Bearer {access-token}
Content-Type: application/json

Rate Limits:

  • 30 requests per minute per user
  • Returns HTTP 429 if exceeded

Troubleshooting

Authentication Failed

Error: Authentication failed. Please check your access token.

Solution:

  1. Verify your token in .env is correct
  2. Check if the token has expired
  3. Generate a new token from the program portal

Rate Limit Exceeded

Error: Rate limit exceeded. Please wait before making more requests.

Solution:

  • The server has built-in rate limiting
  • Wait ~1 minute before making more requests
  • The rate limiter automatically handles this

Program Not Configured

Error: No access token configured for {program}

Solution:

  1. Add the appropriate token to .env
  2. Restart the MCP server
  3. Verify the token variable name matches

Contributing

Contributions are welcome! Please:

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

License

MIT License - see LICENSE file for details

Support

  • Issues: https://github.com/yourusername/advocu-mcp-server/issues
  • Documentation: https://github.com/yourusername/advocu-mcp-server/wiki

Acknowledgments

Roadmap

  • [ ] Microsoft MVP API integration
  • [ ] Activity templates and suggestions
  • [ ] Batch activity submission
  • [ ] Activity analytics and insights
  • [ ] Multi-user support
  • [ ] Web dashboard
  • [ ] Docker container for easy deployment

Made with ā¤ļø for the developer community

Recommended Servers

playwright-mcp

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.

Official
Featured
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

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.

Official
Featured
TypeScript
Kagi MCP Server

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.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

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.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured