Twitter MCP Server

The Twitter MCP Server bridges the gap between AI assistants and the Twitter ecosystem, allowing Claude to perform authenticated actions on behalf of a user. By exposing two core tools— and —the server lets developers embed real‑time social media interaction directly into conversational workflows. This capability is especially valuable for applications that need to monitor brand sentiment, automate announcements, or gather trending data without manual API handling.

At its core, the server authenticates with Twitter’s OAuth 1.0a using four credentials (API key, secret, access token, and token secret). Once authenticated, the MCP exposes a simple interface: one tool to publish a new tweet and another to query recent tweets matching a search term or hashtag. The abstraction keeps the complexities of rate limiting, request signing, and pagination hidden from the AI client, enabling developers to focus on higher‑level logic such as intent detection or content generation.

Key features include:

• Seamless integration: The server registers itself in the client’s configuration, after which Claude can invoke or just like any native tool.
• Security: All credentials are passed via environment variables, keeping secrets out of the codebase.
• Scalability: Because it’s built on MCP, multiple AI assistants can connect concurrently, each maintaining its own authenticated session.
• Extensibility: The open‑source repository allows contributors to add new Twitter endpoints (e.g., direct messages, media uploads) or customize behavior such as retry logic.

Typical use cases span marketing automation—where a chatbot posts campaign updates on demand—to data science pipelines that pull the latest tweets about a product for sentiment analysis. In customer support scenarios, an assistant could search recent mentions to surface relevant complaints or praise in real time. For content creators, the tool can schedule tweets generated by GPT models, ensuring consistent social media presence without manual intervention.

Integration into existing AI workflows is straightforward: once the server is running, Claude can ask the assistant to “post a tweet saying ‘Hello from Claude!’” or “search for tweets about Claude AI,” and the MCP will translate those calls into authenticated Twitter API requests. The response is then fed back to Claude, enabling the assistant to confirm success or provide a list of matching tweets. This tight coupling turns Twitter from a passive data source into an active component of conversational AI, unlocking new possibilities for engagement, automation, and real‑time insight.