Twitter MCP Server

Twitter MCP Server Overview

The Twitter MCP Server bridges the gap between AI assistants and the X (formerly Twitter) platform by exposing a rich set of Twitter operations through the Model Context Protocol. Instead of developers writing custom API wrappers, an LLM can issue declarative tool calls that include the necessary authentication cookies ( and ) directly. This approach lets conversational agents perform real‑world actions—such as posting tweets, retrieving timelines, or managing direct messages—without the assistant needing to handle OAuth flows or token refresh logic.

At its core, the server leverages the unofficial library to communicate with Twitter’s web endpoints. It accepts cookie values supplied by the LLM, validates them via a lightweight authentication test, and then caches the session for subsequent requests. This caching dramatically reduces latency for repeated operations while keeping each user’s credentials isolated. The server therefore solves a common pain point: enabling secure, per‑session Twitter access in a stateless AI workflow without exposing sensitive credentials to the model.

Key capabilities include:

• Timeline and User Content – Retrieve a user’s timeline, search tweets by query or ID, fetch replies, and obtain detailed user profiles.
• Tweet Management – Post new tweets, like or unlike existing ones, retweet or delete retweets, and bookmark content.
• Direct Messaging – Send, retrieve, react to, or delete direct messages, providing a conversational channel between the AI and human users.
• Social Graph Operations – Follow or unfollow accounts, search for users, and gather follower statistics.
• Trending Insights – Pull current trending topics across multiple categories (news, sports, entertainment, for‑you), enabling contextually aware content generation.

These features empower developers to build sophisticated AI experiences such as real‑time social media monitoring, automated content creation, or personalized engagement bots. For example, a marketing assistant could ask the LLM to “post an update about our new product launch and then fetch the top five retweets of that post,” with the MCP server handling all underlying HTTP interactions seamlessly.

Integrating the Twitter MCP Server into an AI workflow is straightforward: the assistant simply invokes a tool with the required arguments, and the server returns structured JSON responses. Because authentication is supplied per call, developers can deploy a single instance that serves multiple users concurrently without risk of credential leakage. The server’s design also emphasizes safety—by relying on cookie‑based authentication, it avoids exposing API keys and limits the scope of each request to the permissions granted by the user’s session.

In summary, the Twitter MCP Server offers a secure, efficient, and developer‑friendly bridge to X’s functionality. Its cookie‑based authentication, session caching, and comprehensive toolset make it an ideal component for building AI applications that need to read from or write to Twitter in a conversational, context‑aware manner.