Backlog MCP Server

The Tmhr1850 Backlog MCP Server bridges the gap between AI assistants and the Backlog project‑management platform. By exposing a rich set of MCP endpoints, it lets Claude and other AI clients perform end‑to‑end project lifecycle operations—creating tickets, updating statuses, fetching user data, and handling attachments—directly from natural‑language prompts. This eliminates the need for manual API calls or custom scripts, enabling developers to build conversational tools that can manage real‑world workflows without leaving the chat interface.

At its core, the server offers a comprehensive suite of tools grouped by domain: project, issue, and search operations. Developers can retrieve a list of spaces or projects, query issues with pagination and sorting, create new tickets with optional priority, assignee, and dates, or update existing ones. The comment tools let AI add contextual notes to issues, while the file‑operation hooks allow attachments to be added or listed. Search capabilities support free‑text queries and fine‑grained filtering by project, status, or assignee, making it easy to surface relevant tickets in a single command.

For AI workflows, the server’s MCP interface is straightforward: each tool accepts JSON‑structured arguments and returns JSON responses that can be parsed by the assistant. This design enables seamless integration into existing conversational pipelines—an AI could, for example, ask a user “Create a bug in Project X” and the assistant would translate that into a call, then confirm with the user. Because all operations are exposed as standard MCP tools, developers can chain actions, handle errors gracefully, and incorporate the data into downstream processes such as automated reporting or notification systems.

Real‑world scenarios that benefit from this MCP server include:

• DevOps automation – A CI/CD pipeline can trigger an issue in Backlog when a build fails, automatically assigning it to the responsible engineer.
• Customer support – Front‑end chatbots can log user complaints as Backlog tickets, ensuring they are tracked in the same system used by developers.
• Project oversight – Managers can ask an AI assistant to list all overdue tasks or generate a sprint report without leaving their chat client.
• Rapid prototyping – New teams can prototype workflow automation by scripting conversational commands that interact with Backlog, speeding up onboarding.

Unique advantages of this server are its native Backlog integration (no OAuth dance, just an API key), a complete feature set that mirrors the Backlog web UI, and its open‑source MIT license, which encourages community contributions. By providing a ready‑to‑use MCP bridge, it empowers developers to unlock Backlog’s full potential in conversational AI environments.