Manage your twitter account programmatically through an MCP (Multi-Channel Platform) server interface.
https://github.com/LuniaKunal/mcp-twitterStop wrestling with Twitter's API complexity every time you need to automate social media workflows. This MCP server gives you clean, programmatic access to your Twitter account through any MCP-compatible tool—from Claude Desktop to custom automation scripts.
You've been there: trying to build Twitter functionality into your workflow, only to get bogged down in OAuth flows, rate limit handling, and API endpoint variations. Meanwhile, your actual use case—whether it's automated posting, sentiment monitoring, or community management—takes a backseat to infrastructure plumbing.
Most Twitter libraries either oversimplify (limiting functionality) or overwhelm you with low-level API details. You end up writing the same authentication and error handling code repeatedly across projects.
This server sits between your tools and Twitter, exposing everything you need through clean MCP tool calls:
The key difference: it's designed for MCP integration first, not as another generic Twitter wrapper.
Content Research Automation: Query trending hashtags in your niche, pull top tweets, analyze engagement patterns, and feed insights directly to your content planning tools. No manual scrolling through Twitter.
Community Management at Scale: Monitor mentions across multiple accounts, auto-respond to common questions, and escalate complex issues to human review. Set up keyword triggers that actually work.
Social Listening for Product Teams: Track competitor mentions, feature requests, and user feedback across Twitter. Pipeline everything into your issue tracker or analytics dashboard without manual copy-paste.
Automated Publishing Workflows: Connect your blog publishing pipeline to Twitter. When you ship new content, automatically craft contextual tweets, engage with early commenters, and track performance metrics.
Add this server to your MCP configuration and immediately gain Twitter capabilities in any MCP-compatible environment:
{
"mcpServers": {
"twitter-mcp": {
"command": "uv",
"args": ["--directory", "path/to/mcp-twitter", "run", "--with", "twikit", "--with", "mcp", "tweet_service.py"],
"env": {
"COOKIES_PATH": "path/to/cookies.json"
}
}
}
}
Your AI assistant can now tweet, search, retrieve timelines, and manage DMs as naturally as it handles file operations or web searches. No separate API clients, no authentication middleware—it's just another tool in your MCP toolkit.
Instead of building Twitter functionality into every tool that needs it, you centralize it once. Your automation scripts, AI assistants, and monitoring tools all get Twitter access through the same interface.
When Twitter changes their API (and they will), you update one server instead of hunting down Twitter code scattered across your infrastructure. When you need to add rate limiting, logging, or filtering, you implement it once for all consumers.
The MCP protocol handles the complexity of tool discovery and communication. Your focus stays on what you're actually building, not on Twitter API quirks.
Get started: Clone the repo, drop in your Twitter credentials, and add it to your MCP server list. Your first automated tweet is about 5 minutes away.