MCP-Twikit: Twitter Intelligence for Your LLM Workflows

Stop switching between your development environment and Twitter when you need social media insights. MCP-Twikit brings Twitter's data and functionality directly into your LLM conversations, letting you search, analyze, and interact with Twitter without breaking your flow.

Why This Matters for Your Workflow

You're probably already using Claude or other LLMs for analysis, but you hit a wall when you need real-time social media data. Instead of manually gathering tweets, copying data, and context-switching between tools, MCP-Twikit lets your AI assistant pull Twitter data directly and perform sophisticated analysis in one conversation.

Real impact: Turn a 30-minute manual research process into a single prompt that delivers structured insights.

What You Get

• Search & Analysis: Query Twitter data with natural language and get structured results
• Sentiment Monitoring: Compare brand sentiment across competitors with a single command
• Profile Intelligence: Deep-dive into user profiles, follower analysis, and engagement patterns
• Timeline Access: Monitor your timeline or specific accounts for relevant updates
• Publishing: Post tweets and manage your Twitter presence from your development environment
• Streaming: Set up filtered streams for real-time monitoring and alerts

Real-World Applications

Competitive Analysis: Compare customer sentiment across multiple ISPs by searching support mentions - the example shows analyzing @IndiHomeCare vs @BiznetHome vs others, ranking them by customer satisfaction in seconds.

Market Research: Track hashtag performance, viral content patterns, or industry discussions without leaving your analysis environment.

Customer Service Intelligence: Monitor brand mentions, analyze complaint patterns, and identify trending issues before they explode.

Content Strategy: Analyze what's working for competitors, identify engagement patterns, and optimize your posting strategy based on real data.

Social Media Automation: Build workflows that post updates, respond to mentions, or alert you to specific keywords or sentiment changes.

Quick Start

Install via Smithery (automatic Claude Desktop integration):

npx -y @smithery/cli install mcp-twikit --client claude

Or manually configure with your Twitter credentials:

{
    "mcpServer": {
        "command": "uvx",
        "args": ["--from", "git+https://github.com/adhikasp/mcp-twikit", "mcp-twikit"],
        "env": {
            "TWITTER_USERNAME": "@your_username",
            "TWITTER_EMAIL": "[email protected]",
            "TWITTER_PASSWORD": "your_password"
        }
    }
}

Example Usage

Once connected, you can ask your AI assistant things like:

• "Compare the sentiment of the last 50 tweets mentioning our competitors"
• "What are people saying about our product launch today?"
• "Show me the most engaging tweets from accounts in our industry this week"
• "Post a tweet about our new feature and track the initial response"

The AI handles the Twitter API calls, data parsing, and analysis - you get actionable insights without the integration overhead.

Integration Benefits

This isn't just another API wrapper. MCP-Twikit integrates Twitter intelligence directly into your existing LLM workflows, whether you're doing market research, competitive analysis, or social media management. Your AI assistant becomes your social media analyst, researcher, and content manager.

Ready to stop manually gathering Twitter data? Install MCP-Twikit and start getting social media insights at the speed of conversation.

MCP-Twikit: 177 stars on GitHub | MIT Licensed | Active development