Bluesky Social MCP

Overview

The Bluesky Social MCP is a purpose‑built server that bridges Claude and other AI assistants to the Bluesky social network. By exposing a rich set of tools—ranging from basic authentication checks to full‑blown post creation and interaction—the server lets developers incorporate real‑time social data into AI workflows without writing custom API wrappers. This is particularly valuable for use cases that require up‑to‑date content, user engagement analytics, or automated moderation within conversational agents.

At its core, the MCP leverages the atproto client library to perform authenticated requests on behalf of a Bluesky user. The server requires only two environment variables: the user’s handle and an app‑specific password, which is generated in the Bluesky settings. Once authenticated, a suite of tools becomes available: profile queries (, ), feed retrieval (, ), and thread navigation (). Each tool maps directly to an atproto method, ensuring that the MCP remains lightweight while still offering comprehensive coverage of Bluesky’s public API surface.

For content creation, the server supports a full media pipeline. Developers can send plain text posts (), embed single or multiple images (, ), and even attach videos (). Post management tools such as , , and allow AI assistants to interact with content dynamically—useful for automated curation, sentiment analysis, or community moderation. The inclusion of reverse‑lookup tools (, ) provides richer context for AI models when evaluating post popularity or influence.

Real‑world scenarios abound. A conversational agent could automatically surface the latest posts from a user’s timeline, summarize trending discussions, or curate personalized content feeds. A chatbot integrated into a marketing platform could schedule posts, track engagement metrics, and suggest optimal posting times. Moderation bots can fetch user profiles, follow or mute problematic accounts, and delete inappropriate content—all orchestrated through a single MCP interface. Because the server’s tools are stateless and expose only the necessary parameters, developers can compose complex workflows in a declarative manner, keeping their AI code clean and focused on intent rather than API plumbing.

Unique to this MCP is its full coverage of Bluesky’s public methods coupled with an emphasis on developer ergonomics. The server is version‑pinned for stability, and the README highlights that all tools have been implemented and tested against the live Bluesky service. This guarantees reliable operation in production environments. Moreover, by using standard MCP conventions (e.g., configuration), the server integrates seamlessly into existing AI assistant ecosystems, allowing for rapid prototyping and deployment of socially aware conversational agents.