Twitter MCP

What kunallunia/twitter-mcp does

The kunallunia/twitter-mcp MCP server connects an MCP-compatible agent to Twitter account and content operations. It is intended for programmatic management rather than a standalone web interface, and the repository describes support for both reading Twitter data and changing account content.

Read operations include retrieving the authenticated account’s home timeline, fetching posts from any public user, and searching for posts containing a hashtag. The server can also retrieve replies to posts and produce summarized insights from those replies. The project description additionally identifies conversation analysis and sentiment analysis for posts as supported functionality.

Write operations cover direct messages and the post lifecycle. An agent can send and receive Twitter DMs, publish new posts, and delete posts created by the account. The available capabilities make the kunallunia/twitter-mcp MCP server relevant to monitoring, lightweight social workflows, and agent-assisted account management.

How it works

The repository is a Python project and lists Python 3.11 or newer among its prerequisites. Its launch example runs tweet_service.py with uv, adding the twikit and mcp dependencies at runtime. The README also lists uvicorn as a prerequisite, although the shown launch command uses uv directly.

Twitter credentials are configured in a .env file. The supplied MCP configuration passes two environment values to the process: COOKIES_PATH, which points to a cookies file, and ENV_FILE, which identifies the environment file. The example uses Windows-style path placeholders, so they must be replaced with paths valid in the deployment environment.

Setup and configuration

To set up the kunallunia/twitter-mcp MCP server, clone the repository and install the dependencies from requirements.txt with pip. Create the environment file using .env.example as a reference, then provide the required Twitter API credentials. The README does not enumerate the individual credential variable names, so those names should be taken from the repository’s example configuration rather than inferred.

The MCP client configuration starts the local Python service with uv, points it at the project’s source directory, and supplies COOKIES_PATH and ENV_FILE in the process environment. The documented command contains a placeholder path and is therefore a template rather than a directly runnable command without editing.

Tools and capabilities

The documented feature set includes:

• Reading the Twitter home timeline.
• Fetching tweets from any public user.
• Searching posts by hashtag.
• Retrieving replies and generating summaries.
• Sending and receiving direct messages.
• Creating and deleting posts.
• Analyzing conversations and post sentiment, as stated in the project description.

These capabilities cover both observation and account actions. Write operations should be enabled only when the configured Twitter credentials and account permissions are appropriate for the intended workflow.

Limitations and notes

The material does not list individual MCP tool names, input schemas, response formats, rate-limit behavior, or supported Twitter API plans. It also does not identify specific MCP clients by name. The repository requires Twitter credentials and cookie configuration, but the excerpt does not explain how cookies are obtained, refreshed, or secured. Verify those details in the project files before deploying an automated workflow that sends messages, publishes posts, or deletes content.

Getting started with this kunallunia/twitter-mcp MCP server

Always refer to the official documentation for the most accurate and up-to-date information.