x-twitter-posting-mcp

<h1 align="center">X-Twitter-Posting-MCP: Post to Twitter from AI Agents</h1>

<p align="center"> <img src="public/TwitterAndMCP.png" alt="Twitter and MCP Integration" width="600"> </p>

A template implementation of the Model Context Protocol (MCP) server for posting tweets and threads to X (formerly Twitter).

Overview

This project demonstrates how to build an MCP server that enables AI agents to post tweets and threads to X (Twitter). It serves as a practical template for creating your own Twitter-posting MCP servers.

The implementation follows the best practices laid out by Anthropic for building MCP servers, allowing seamless integration with any MCP-compatible client.

Features

The server provides two essential Twitter posting tools:

1. post_tweet: Post a single tweet to X (Twitter)
2. post_thread: Post a thread of tweets to X (Twitter)

Prerequisites

• Python 3.12+
• X (Twitter) API keys and tokens
• Docker if running the MCP server as a container (recommended)

Installation

Using uv

1. Install uv if you don't have it:

   pip install uv
   

2. Clone this repository:

   git clone https://github.com/DevRico003/x-twitter-posting-mcp.git
   cd x-twitter-posting-mcp
   

3. Install dependencies:

   uv pip install -e .
   

4. Create a .env file based on .env.example:

   cp .env.example .env
   

5. Configure your environment variables in the .env file (see Configuration section)

Using Docker (Recommended)

1. Build the Docker image:

   docker build -t mcp/x-twitter -t --build-arg PORT=8050 .
   

2. Create a .env file based on .env.example and configure your environment variables

Configuration

The following environment variables can be configured in your .env file:

Variable	Description	Example
TRANSPORT	Transport protocol (sse or stdio)	sse
HOST	Host to bind to when using SSE transport	0.0.0.0
PORT	Port to listen on when using SSE transport	8050
TWITTER_API_KEY	Your Twitter/X API key	AbCdEfGhIjKlMnOpQrStUvWxYz
TWITTER_API_KEY_SECRET	Your Twitter/X API key secret	AbCdEfGhIjKlMnOpQrStUvWxYz
TWITTER_ACCESS_TOKEN	Your Twitter/X access token	123456789-AbCdEfGhIjKlMnOpQrStUvWxYz
TWITTER_ACCESS_TOKEN_SECRET	Your Twitter/X access token secret	AbCdEfGhIjKlMnOpQrStUvWxYz

Running the Server

Using uv

SSE Transport

# Set TRANSPORT=sse in .env then:
uv run src/main.py

The MCP server will be available as an API endpoint that you can connect to with the configuration shown below.

Stdio Transport

With stdio, the MCP client itself can spin up the MCP server, so nothing to run at this point.

Using Docker

SSE Transport

docker run --env-file .env -p:8050:8050 mcp/x-twitter

The MCP server will be available as an API endpoint within the container that you can connect to with the configuration shown below.

Stdio Transport

With stdio, the MCP client itself can spin up the MCP server container, so nothing to run at this point.

Integration with MCP Clients

SSE Configuration

Once you have the server running with SSE transport, you can connect to it using this configuration:

{
  "mcpServers": {
    "x-twitter": {
      "transport": "sse",
      "url": "http://localhost:8050/sse"
    }
  }
}

Note for Windsurf users: Use serverUrl instead of url in your configuration:

{
  "mcpServers": {
    "x-twitter": {
      "transport": "sse",
      "serverUrl": "http://localhost:8050/sse"
    }
  }
}

Note for n8n users: Use host.docker.internal instead of localhost since n8n has to reach outside of it's own container to the host machine:

So the full URL in the MCP node would be: http://host.docker.internal:8050/sse

Make sure to update the port if you are using a value other than the default 8050.

Python with Stdio Configuration

Add this server to your MCP configuration for Claude Desktop, Windsurf, or any other MCP client:

{
  "mcpServers": {
    "x-twitter": {
      "command": "your/path/to/x-twitter-posting-mcp/.venv/Scripts/python.exe",
      "args": ["your/path/to/x-twitter-posting-mcp/src/main.py"],
      "env": {
        "TRANSPORT": "stdio",
        "TWITTER_API_KEY": "YOUR-API-KEY",
        "TWITTER_API_KEY_SECRET": "YOUR-API-KEY-SECRET",
        "TWITTER_ACCESS_TOKEN": "YOUR-ACCESS-TOKEN",
        "TWITTER_ACCESS_TOKEN_SECRET": "YOUR-ACCESS-TOKEN-SECRET"
      }
    }
  }
}

Docker with Stdio Configuration

{
  "mcpServers": {
    "x-twitter": {
      "command": "docker",
      "args": ["run", "--rm", "-i", 
               "-e", "TRANSPORT", 
               "-e", "TWITTER_API_KEY", 
               "-e", "TWITTER_API_KEY_SECRET", 
               "-e", "TWITTER_ACCESS_TOKEN", 
               "-e", "TWITTER_ACCESS_TOKEN_SECRET", 
               "mcp/x-twitter"],
      "env": {
        "TRANSPORT": "stdio",
        "TWITTER_API_KEY": "YOUR-API-KEY",
        "TWITTER_API_KEY_SECRET": "YOUR-API-KEY-SECRET",
        "TWITTER_ACCESS_TOKEN": "YOUR-ACCESS-TOKEN",
        "TWITTER_ACCESS_TOKEN_SECRET": "YOUR-ACCESS-TOKEN-SECRET"
      }
    }
  }
}

Usage Examples

Here are some examples of how to use the MCP tools from an AI agent:

Post a Single Tweet

# Create and post a tweet
result = await mcp.invoke("x-twitter", "post_tweet", {"text": "Hello, Twitter! This is a tweet sent via MCP."})
print(result)

Post a Thread

# Create and post a thread
tweets = [
    "This is the first tweet in a thread posted via MCP.", 
    "This is the second tweet in the thread.", 
    "This is the final tweet in the thread."
]
result = await mcp.invoke("x-twitter", "post_thread", {"tweets": tweets})
print(result)