Red5d/me-mcp
If you are the rightful owner of me-mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
A self-hosted MCP server providing AI assistants with access to personal information and a secure contact mechanism.
Me MCP
Personal Information MCP Server
A self-hosted MCP (Model Context Protocol) server allowing AI assistants to access personal information that you supply, and receive contact requests.
Overview
This MCP server provides AI assistants with structured access to your personal details like bio, skills, and contact methods, while also offering a secure way for others to send you messages through your configured webhook.
Features
- 📋 Personal Info API: Expose your professional details to AI assistants
- 📬 Contact Mechanism: Let people reach you without directly sharing your email
- 🔐 Privacy Control: Configure exactly what information you want to share
- 🤖 AI-Friendly Interface: Pre-built prompts and resources for modern AI systems
Installation
-
Clone this repository:
git clone https://github.com/yourusername/me-mcp.git cd me-mcp
-
Create and configure your
config.json
file:cp config.json.example config.json nano config.json # Edit with your information
Configuration
Edit config.json
with your personal information and webhook URL. The "name" field is required, all others are optional and can be added/removed as needed:
{
"webhook_url": "https://your-webhook-endpoint.com",
"personal_info": {
"name": "Your Name",
"handle": "yourhandle",
"contact_methods": {
"github": "https://github.com/yourhandle",
"matrix": "https://matrix.to/#/@yourhandle:example.com",
"X": "https://x.com/yourhandle",
"email": "you@example.com"
},
"occupation": "Your Job",
"skills": ["Your", "Skills", "Here"],
"interests": ["Your", "Interests", "Here"],
"bio": "A short biography about yourself."
}
}
Usage
Run the MCP server:
uv run mcp run -t sse me_mcp.py
Your MCP server will be available via SSE at http://0.0.0.0:8000
which you can then expose to remote LLMs using a reverse proxy or similar.
You can also use mcp-proxy which includes a few more configuration options to run the server.
MCP Tools
- about_me(): Returns your configured personal information
- contact(): Allows sending you messages via webhook
MCP Resources
- about://me: JSON resource containing your personal information
MCP Prompts
- about_me_prompt(): Asks the AI to describe your information
- send_message(): Guides the AI to help someone contact you
Security Considerations
- Set up a secure webhook endpoint that processes contact requests
- Only expose information you're comfortable sharing publicly
- Consider running behind a reverse proxy with rate limiting
License
MIT