ActivityPub MCP Server - Fediverse Client

The ActivityPub MCP Server is a purpose‑built bridge that lets large language models, such as Claude, talk directly to the Fediverse. By exposing a full Model Context Protocol (MCP) interface—complete with resources, tools, prompts, and completion logic—the server removes the need for developers to write custom HTTP clients or manage OAuth flows. Instead, an LLM can request “discover the actor @alice@mastodon.social” or “fetch the latest 20 posts from @bob@misskey.io” and receive structured JSON responses that can be fed back into the conversation. This capability is especially valuable for assistants that need to surface real‑time social content, curate feeds, or answer questions about a user’s activity across multiple federated platforms.

At its core, the server implements a lightweight ActivityPub client that handles the nuances of the protocol—WebFinger discovery, instance introspection, timeline fetching, and follower/following lists. It supports Mastodon, Pleroma, Misskey, and any server that adheres to ActivityPub, making it a universal entry point into the decentralized social web. The MCP layer adds LLM‑optimized tooling: prompts are pre‑configured for common discovery patterns, while tools expose atomic actions such as “search posts by keyword” or “retrieve instance statistics.” The completion mechanism ensures that argument values are inferred and validated, reducing the risk of malformed requests.

Key features include high‑performance caching to keep latency low, built‑in security checks that sanitize inputs, and detailed monitoring hooks for observability. The server’s TypeScript foundation guarantees type safety across the API surface, while its modular design allows developers to plug in additional MCP resources or extend existing ones. By leveraging the MCP protocol, the ActivityPub server seamlessly integrates into any AI workflow that already consumes MCP endpoints—whether it’s a chatbot, data‑aggregation pipeline, or automated moderation tool.

Real‑world use cases abound: an AI assistant could answer “What did @charlie say yesterday?” by querying the Fediverse, or a content‑curation bot could surface trending topics across multiple instances for a newsletter. Researchers studying social dynamics can programmatically gather interaction graphs, and developers building federated social apps can prototype new features without handling the protocol intricacies. The server’s ability to expose both actor data and instance metadata makes it uniquely suited for exploratory analytics, compliance monitoring, or building hybrid human‑AI collaboration tools that span the decentralized web.

In summary, the ActivityPub MCP Server turns the complex world of federated social networking into a simple, LLM‑friendly API. By unifying discovery, data retrieval, and prompt tooling under the MCP umbrella, it empowers developers to build intelligent applications that can read from, write to, and analyze the Fediverse with minimal friction.