esa MCP Server

The esa MCP Server bridges Claude AI with the esa collaboration platform, turning natural‑language queries into concrete API calls that manipulate documents within an esa team. By exposing a set of well‑defined tools—such as listing posts, retrieving details, creating new entries, and updating existing ones—the server removes the friction of manual API usage. Developers can now embed document management directly into conversational flows, allowing an AI assistant to fetch the latest project notes, add a new task card, or edit a wiki page without leaving the chat interface.

At its core, the server translates MCP commands into HTTP requests against the esa REST API. Each tool accepts a small, typed input schema (e.g., , , or optional filters like and ) and returns a JSON payload that the AI can interpret. This tight coupling means Claude can reason about document metadata, propose edits based on context, or even orchestrate multi‑step workflows—such as creating a draft post and then tagging it for review—all while maintaining the conversational tone that users expect.

Key capabilities include:

• Comprehensive post management: Search, list, create, and update posts with fine‑grained control over tags, categories, and WIP status.
• Comment handling: Retrieve comments for a post, enabling the assistant to surface discussions or add new feedback.
• Rich filtering and sorting: Customizable query parameters allow the AI to surface the most relevant documents quickly.
• Extensibility: The MCP framework makes it straightforward to add new esa endpoints or extend existing tools as the platform evolves.

Real‑world scenarios that benefit from this integration are plentiful. A project manager could ask Claude to pull the latest sprint notes, then have the assistant draft a summary email. A developer might request that Claude create a new issue post and tag it for the QA team, all from within a chat. In educational settings, instructors could let the AI populate course materials or update lecture notes on the fly.

Because the server adheres strictly to MCP, it fits seamlessly into any AI workflow that already consumes MCP services. Whether you’re building a custom assistant, augmenting an existing chatbot, or orchestrating automated documentation pipelines, the esa MCP Server provides a reliable, typed bridge between conversational AI and your team’s knowledge base.