Gopher AI (Twitter Search)

A Model Context Protocol (MCP) server that provides access to the Gopher AI API. This server allows MCP clients to search data through the Gopher AI platform.

Features

• Twitter Search: Search Twitter posts using natural language queries
• MCP Integration: Fully compatible with Model Context Protocol clients
• Configurable Results: Adjustable maximum number of search results
• Error Handling: Comprehensive error handling and reporting
• Async Processing: Handles asynchronous API responses with polling

Prerequisites

• Go 1.24.7 or later
• Gopher AI API key
• MCP-compatible client (e.g., Claude Desktop, Cline, etc.)

Installation

From Source

1. Clone the repository:

git clone https://github.com/gopher-lab/gopher-mcp-server.git
cd gopher-mcp-server

2. Build the server:

go build -o gopher-mcp-server ./data

Using Docker

docker build -t gopher-mcp-server .

Configuration

Environment Variables

• GOPHER_API: Required - Your Gopher AI API key
• MAX_RESULTS: Optional - Maximum number of search results to return (default: 15)

Example Configuration

export GOPHER_API="your-gopher-api-key-here"
export MAX_RESULTS="20"

Usage

Running the Server

# Using the binary
./gopher-mcp-server

# Using Docker
docker run -e GOPHER_API="your-api-key" gopher-mcp-server

MCP Client Configuration

Add this server to your MCP client configuration:

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "gopher-twitter": {
      "command": "./gopher-mcp-server",
      "env": {
        "GOPHER_API": "your-gopher-api-key-here",
        "MAX_RESULTS": "15"
      }
    }
  }
}

Cline Configuration

{
  "mcpServers": {
    "gopher-twitter": {
      "command": "docker",
      "args": ["run", "--rm", "-e", "GOPHER_API=your-api-key", "gopher-mcp-server"],
      "env": {
        "GOPHER_API": "your-gopher-api-key-here"
      }
    }
  }
}

Available Tools

search_twitter

Searches Twitter posts using the Gopher AI API.

Parameters:

• query (string): The search query to execute

Returns:

• tweets (array): Array of Twitter posts matching the search query
• error (string, optional): Error message if the search fails

Example Usage:

{
  "name": "search_twitter",
  "arguments": {
    "query": "artificial intelligence trends 2024"
  }
}

Response Example:

{
  "tweets": [
    {
      "ID": "tweet_123",
      "Content": "Exciting developments in AI this year...",
      "Metadata": {...},
      "Score": 0.95
    }
  ],
  "error": null
}

API Details

Twitter Post Structure

Each Twitter post in the response contains:

• ID: Unique identifier for the post
• Content: The text content of the tweet
• Metadata: Additional metadata about the post
• Score: Relevance score for the search query

Error Handling

The server handles various error scenarios:

• API Errors: Invalid API keys, rate limiting, service unavailable
• Network Errors: Connection timeouts, network failures
• Processing Errors: Search timeout, invalid responses

Error messages are returned in the error field of the response.

Development

Building

# Build the server
make build

# Run tests
make test

# Build Docker image
make docker-build

Dependencies

• github.com/modelcontextprotocol/go-sdk: MCP SDK for Go
• github.com/tmc/langchaingo: Language chain utilities

Troubleshooting

Common Issues

1. API Key Not Set

   • Ensure GOPHER_API environment variable is set
   • Verify the API key is valid and has proper permissions

2. Search Timeout

   • The server polls for results up to 30 times (60 seconds total)
   • Check if the Gopher AI service is experiencing delays

3. No Results Returned

   • Verify the search query is valid
   • Check if there are any posts matching your criteria
   • Ensure the API key has access to Twitter data

4. MCP Client Connection Issues

   • Verify the server binary is executable
   • Check that the MCP client configuration is correct
   • Ensure the server is running and accessible

Debugging

Enable verbose logging by setting the log level:

export LOG_LEVEL=debug
./gopher-mcp-server

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 Apache License 2.0. See the LICENSE file for details.

Support

For issues and questions:

• Create an issue on GitHub
• Check the Gopher AI documentation for API-related questions
• Review MCP documentation for protocol-related issues