What is Twitter Mcp Server For Claude

The Twitter Trends Analysis MCP Server is a Python-based application that connects to Twitter’s API to fetch real-time trending topics and leverages the analysis capabilities of Claude. It allows businesses and developers to gain insights into current trends and identify potential opportunities based on social media discussions.

Use cases

This MCP server can be used in various scenarios, such as identifying business opportunities by analyzing trending topics relevant to specific industries, conducting market research by tracking public sentiment around products or services, and aiding content creators or marketers in strategizing their campaigns based on popular trends.

How to use

To utilize the server, set up the project environment, install necessary Python packages, and configure your Twitter API credentials. Run the server using the command line, and then connect it to Claude Desktop to analyze Twitter trends by using specific commands related to business opportunities or insights into current events.

Key features

Key features include real-time fetching of Twitter trends, category-based analysis for different sectors, AI-powered insights through Claude, detailed logging for monitoring server activity, and the ability to respond to user commands with tailored analysis of trending topics.

Where to use

The server can be applied in business environments, marketing agencies, research institutions, and by content creators who wish to stay updated on social media trends. It is particularly effective for sectors like technology, entertainment, and consumer goods where understanding public interests is crucial for strategy development.

Building a Twitter Trends Analysis MCP Server for Claude

This tutorial will guide you through creating a Model Context Protocol (MCP) server that connects Twitter’s trending topics with Claude’s analysis capabilities. The server will fetch real-time Twitter trends and use Claude to analyze them for business opportunities.

Prerequisites

• Python 3.8 or higher
• Claude Desktop installed
• Twitter Developer Account with API access
• Basic understanding of Python

Part 1: Setting Up the Environment

1. Create a new project directory:

mkdir twitter-trends-mcp
cd twitter-trends-mcp

2. Set up a virtual environment:

python -m venv .venv
.venv\Scripts\activate  # On Windows

3. Install required packages:

pip install tweepy mcp python-dotenv hatchling

Part 2: Project Structure

Create the following directory structure:

twitter-trends-mcp/
├── pyproject.toml
├── twitter_server_run.py
├── src/
│   └── twitter_trends_mcp/
│       ├── __init__.py
│       └── server.py

Part 3: Configuration Files

1. Create pyproject.toml in the root directory:

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "twitter-trends-mcp"
version = "0.1.0"
description = "Twitter Trends MCP Server"
requires-python = ">=3.8"
dependencies = [
    "tweepy",
    "mcp",
    "python-dotenv"
]

[tool.hatch.build]
packages = ["src/twitter_trends_mcp"]
include = ["src/twitter_trends_mcp/*"]

[project.scripts]
twitter-trends-server = "twitter_trends_mcp:main"

2. Create src/twitter_trends_mcp/__init__.py:

"""Twitter Trends MCP Server package."""
import asyncio
from . import server

def main():
    """Main entry point for the package."""
    asyncio.run(server.main())

__all__ = ['main', 'server']

3. Create entry point file twitter_server_run.py:

#!/usr/bin/env python
import os
import sys
import logging
from pathlib import Path

# Configure logging
logging.basicConfig(
    level=logging.DEBUG,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler('twitter_server.log'),
        logging.StreamHandler()
    ]
)
logger = logging.getLogger('twitter-trends-mcp')

# Add the src directory to the Python path
src_path = str(Path(__file__).parent / "src")
sys.path.insert(0, src_path)
logger.info(f"Python path: {sys.path}")

try:
    from twitter_trends_mcp.server import main
    logger.info("Successfully imported server module")
except Exception as e:
    logger.error(f"Error importing server module: {e}")
    raise

if __name__ == "__main__":
    try:
        logger.info("Starting server...")
        import asyncio
        asyncio.run(main())
    except KeyboardInterrupt:
        logger.info("Server stopped by user")
    except Exception as e:
        logger.error(f"Server error: {e}")
        raise

Part 4: Twitter API Setup

1. Go to Twitter Developer Portal
2. Create a new project and app
3. Get your API credentials:
   • API Key
   • API Secret
   • Access Token
   • Access Token Secret
   • Bearer Token

Part 5: MCP Server Implementation

Create src/twitter_trends_mcp/server.py with the complete server code, including:

• API client initialization
• Trend fetching logic
• Resource and tool handlers
• Analysis integration with Claude

Key components:

# Initialize Twitter clients
client_v2 = tweepy.Client(...)
auth = tweepy.OAuthHandler(...)
api_v1 = tweepy.API(auth)

# Define server capabilities
app = Server("twitter-trends-server")

# Implement handlers
@app.list_resources()
async def list_resources() -> list[Resource]: ...

@app.read_resource()
async def read_resource(uri: AnyUrl) -> str: ...

@app.list_tools()
async def list_tools() -> list[Tool]: ...

@app.call_tool()
async def call_tool(name: str, arguments: Any) -> Sequence[TextContent]: ...

Part 6: Claude Desktop Configuration

1. Locate your Claude Desktop config file:

   • Windows: %APPDATA%\Claude\claude_desktop_config.json
   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

2. Update the configuration:

{
  "mcpServers": {
    "twitter-trends": {
      "command": "C:\\Users\\YOUR_USERNAME\\twitter-trends-mcp\\.venv\\Scripts\\python.exe",
      "args": [
        "C:\\Users\\YOUR_USERNAME\\twitter-trends-mcp\\twitter_server_run.py"
      ],
      "env": {
        "PYTHONPATH": "C:\\Users\\YOUR_USERNAME\\twitter-trends-mcp\\src",
        "PYTHONUNBUFFERED": "1"
      },
      "cwd": "C:\\Users\\YOUR_USERNAME\\twitter-trends-mcp"
    }
  }
}

Part 7: Running and Testing

1. Install the package:

pip install -e .

2. Run server:

python twitter_server_run.py

3. In Claude Desktop:

   • Click the 🔌 icon
   • Look for “twitter-trends”
   • Try: “Analyze current Twitter trends for SaaS opportunities”

4. Monitor logs:

Get-Content twitter_server.log -Wait

Troubleshooting Tips

1. Common Issues:

   • Module not found: Check PYTHONPATH
   • Connection errors: Verify paths in config
   • API errors: Validate credentials
   • Server not responding: Check logs

2. Log Locations:

   • Server: twitter_server.log
   • Claude: %APPDATA%\Claude\Logs\mcp*.log

Features

• Real-time trend fetching
• Category-based analysis
• Business opportunity identification
• AI-powered insights
• Detailed logging

Best Practices

1. Use absolute paths
2. Keep credentials secure
3. Monitor logs
4. Test incrementally
5. Use virtual environments

Next Steps

• Add trend history
• Implement sentiment analysis
• Support more regions
• Add business metrics
• Enhance analysis categories