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Redmine MCP Server

MCP Server

Real‑time issue and wiki data via Model Context Protocol

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Updated Dec 25, 2024

About

The Redmine MCP Server plugin exposes a Model Context Protocol interface using server‑side events, allowing clients to list issues and wiki pages or read individual items in real time from a Redmine instance.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview

The Redmine MCP Server is an experimental plugin that exposes Redmine’s core issue‑tracking and wiki functionality through the Model Context Protocol (MCP). By converting Redmine data into MCP tools, the server enables AI assistants—such as Claude—to query and manipulate project information in real time without leaving their conversational context. This bridge removes the need for separate API keys or custom adapters, allowing developers to treat Redmine as a first‑class data source within AI‑driven workflows.

At its core, the server leverages Rails’ Server Side Events (SSE) to stream MCP responses. This choice keeps the connection lightweight and avoids the pitfalls of traditional HTTP polling, while still being compatible with Ruby on Rails’ action controller infrastructure. Although the plugin is labeled experimental and currently lacks authentication, it demonstrates how a simple SSE endpoint can deliver structured tool definitions and results that an AI client can consume seamlessly.

Key capabilities include four dedicated tools:

  • – retrieves a complete list of issues for a specified project.
  • – enumerates all wiki pages associated with a project.
  • – fetches the full details of a single issue, including status, assignee, and comments.
  • – returns the content of a specified wiki page.

Each tool is defined in plain JSON, making it straightforward for an AI to call the correct function with minimal context. The server’s design emphasizes simplicity: developers can drop the plugin into a Redmine instance, start the application, and immediately have an MCP endpoint available for integration.

Typical use cases involve AI‑powered project management assistants that can answer questions like “What are the open bugs in Project X?” or “Show me the latest updates on the project wiki.” By feeding these tool outputs back into an AI model, developers can build conversational agents that not only provide information but also suggest next steps, update issue statuses, or generate status reports—all within a single chat session. The real‑time streaming nature of SSE ensures that responses are delivered promptly, which is critical for maintaining a fluid conversational experience.

Unique advantages of this server include its tight coupling with Redmine’s native data structures and the fact that it requires no additional API layer. Because the plugin directly taps into Redmine’s database through ActiveRecord, it guarantees consistency and up‑to‑date information. Furthermore, the use of SSE keeps bandwidth usage low while still supporting continuous data feeds, making it well suited for large projects where issue lists or wiki pages can be extensive. For developers looking to integrate a robust project tracker into an AI workflow without reinventing the wheel, the Redmine MCP Server offers a lightweight yet powerful starting point.