x-twitter-posting-mcp
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
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.
Related MCP server: Agent Twitter Client MCP
Features
The server provides two essential Twitter posting tools:
post_tweet: Post a single tweet to X (Twitter)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
Install uv if you don't have it:
pip install uvClone this repository:
git clone https://github.com/DevRico003/x-twitter-posting-mcp.git cd x-twitter-posting-mcpInstall dependencies:
uv pip install -e .Create a
.envfile based on.env.example:cp .env.example .envConfigure your environment variables in the
.envfile (see Configuration section)
Using Docker (Recommended)
Build the Docker image:
docker build -t mcp/x-twitter -t --build-arg PORT=8050 .Create a
.envfile based on.env.exampleand configure your environment variables
Configuration
The following environment variables can be configured in your .env file:
Variable | Description | Example |
| Transport protocol (sse or stdio) |
|
| Host to bind to when using SSE transport |
|
| Port to listen on when using SSE transport |
|
| Your Twitter/X API key |
|
| Your Twitter/X API key secret |
|
| Your Twitter/X access token |
|
| Your Twitter/X access token secret |
|
Running the Server
Using uv
SSE Transport
# Set TRANSPORT=sse in .env then:
uv run src/main.pyThe 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-twitterThe 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
serverUrlinstead ofurlin 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)This server cannot be deployed
Maintenance
Related MCP Connectors
Hosted X (Twitter) MCP server for Claude, ChatGPT and Cursor, with each action switched per account.
Hosted MCP server for AI agents to post to LinkedIn profiles and X and upload to YouTube.
FastMCP server for posting formatted content to X (Twitter) — Tollbooth-monetized, DPYC-native
Publish and schedule tweets and threads on X (Twitter) from your AI assistant.
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