Mentioned as a cloud deployment option for hosting the MCP server
Referenced for community support and getting help with Puch AI
Used for environment variable configuration including authentication tokens
Mentioned as a cloud deployment option for hosting the MCP server
Used to expose the local MCP server over HTTPS tunneling for external access
The MCP server is implemented in Python and requires Python 3.11 or higher
Mentioned as a cloud deployment option for hosting the MCP server
Mentioned as a cloud deployment option for hosting the MCP server
Integrates with Puch AI WhatsApp bot for AI assistant interactions and requires WhatsApp number configuration
MCP Starter for Puch AI
This is a starter template for creating your own Model Context Protocol (MCP) server that works with Puch AI. It comes with ready-to-use tools for job searching and image processing.
What is MCP?
MCP (Model Context Protocol) allows AI assistants like Puch to connect to external tools and data sources safely. Think of it like giving your AI extra superpowers without compromising security.
What's Included in This Starter?
🎯 Job Finder Tool
- Analyze job descriptions - Paste any job description and get smart insights
- Fetch job postings from URLs - Give a job posting link and get the full details
- Search for jobs - Use natural language to find relevant job opportunities
🖼️ Image Processing Tool
- Convert images to black & white - Upload any image and get a monochrome version
🔐 Built-in Authentication
- Bearer token authentication (required by Puch AI)
- Validation tool that returns your phone number
Quick Setup Guide
Step 1: Install Dependencies
First, make sure you have Python 3.11 or higher installed. Then:
Step 2: Set Up Environment Variables
Create a .env
file in the project root:
Then edit .env
and add your details:
Important Notes:
AUTH_TOKEN
: This is your secret token for authentication. Keep it safe!MY_NUMBER
: Your WhatsApp number in format{country_code}{number}
(e.g.,919876543210
for +91-9876543210)
Step 3: Run the Server
You'll see: 🚀 Starting MCP server on http://0.0.0.0:8086
Step 4: Make It Public (Required by Puch)
Since Puch needs to access your server over HTTPS, you need to expose your local server:
Option A: Using ngrok (Recommended)
- Install ngrok: Download from https://ngrok.com/download
- Get your authtoken:
- Go to https://dashboard.ngrok.com/get-started/your-authtoken
- Copy your authtoken
- Run:
ngrok config add-authtoken YOUR_AUTHTOKEN
- Start the tunnel:
Option B: Deploy to Cloud
You can also deploy this to services like:
- Railway
- Render
- Heroku
- DigitalOcean App Platform
How to Connect with Puch AI
- Open Puch AI in your browser
- Start a new conversation
- Use the connect command:
Debug Mode
To get more detailed error messages:
Customizing the Starter
Adding New Tools
- Create a new tool function:
- Add required imports if needed
📚 Additional Documentation Resources
Official Puch AI MCP Documentation
- Main Documentation: https://puch.ai/mcp
- Protocol Compatibility: Core MCP specification with Bearer & OAuth support
- Command Reference: Complete MCP command documentation
- Server Requirements: Tool registration, validation, HTTPS requirements
Technical Specifications
- JSON-RPC 2.0 Specification: https://www.jsonrpc.org/specification (for error handling)
- MCP Protocol: Core protocol messages, tool definitions, authentication
Supported vs Unsupported Features
✓ Supported:
- Core protocol messages
- Tool definitions and calls
- Authentication (Bearer & OAuth)
- Error handling
✗ Not Supported:
- Videos extension
- Resources extension
- Prompts extension
Getting Help
- Join Puch AI Discord: https://discord.gg/VMCnMvYx
- Check Puch AI MCP docs: https://puch.ai/mcp
- Puch WhatsApp Number: +91 99988 81729
Happy coding! 🚀
Use the hashtag #BuildWithPuch
in your posts about your MCP!
This starter makes it super easy to create your own MCP server for Puch AI. Just follow the setup steps and you'll be ready to extend Puch with your custom tools!
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A starter template for creating MCP servers that work with Puch AI, featuring built-in tools for job searching and image processing. Includes job description analysis, job posting fetching, job search capabilities, and image-to-grayscale conversion with bearer token authentication.
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