Your AI shouldn't just read tickets.
It should work them.

redmine-mcp-server gives AI agents 45 tools to triage, update, comment on, and close Redmine issues — the way a project manager would.

pip install redmine-mcp-server
Scripted walkthrough — no real Redmine is connected.
An AI agent on a live Redmine
it sees the same Issues page you do — and edits it with MCP tool calls
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✻ Welcome to Claude Coderedmine-mcp-server connected over MCP · 45 tools available
▸ press Run the agent to start
▏
? for shortcuts● redmine-mcp-server (MCP)
0tool calls
0issues touched
0comments added
0issues closed
This is a scripted walkthrough against canned data. The JSON in each tool call matches the real server's response shape field-for-field — including the <insecure-content> boundary tags that wrap untrusted user text. Nothing here connects to a live Redmine.

Wire it into your agent.

One command. Claude Desktop, Claude Code, Cursor, VS Code, Codex.

pip install redmine-mcp-server

The demo shows 4 of the server's 45 tools. The full set spans list_redmine_issues, get_redmine_issue, update_redmine_issue, manage_time_entry, manage_redmine_wiki_page, manage_project_member, search_entire_redmine, and more — covering issues, projects, wikis, time tracking, versions, and CRM, plus OAuth multi-tenant auth and a read-only safety mode.

GitHub PyPI Docs Blog
About redmine-mcp-server

redmine-mcp-server: Redmine project management for AI agents

redmine-mcp-server is an open-source MCP (Model Context Protocol) server that lets AI agents read and manage a Redmine instance: issues, projects, wikis, time tracking, versions, and contacts. It ships as a Python package and connects to Claude Desktop, Claude Code, Cursor, VS Code Copilot, Codex CLI, and any MCP-compatible client.

What it does

Redmine has a capable REST API, but wiring an agent to it directly means handing the model raw HTTP access — which is slow, error-prone, and unsafe. redmine-mcp-server exposes 45 purpose-built tools instead. An agent can list and filter issues, read a ticket with its full history, update status and assignee, add notes, log time, manage wiki pages, and run global search — each as a single typed tool call with predictable, serialized JSON.

What the demo shows

The browser demo is a scripted simulation of a triage workflow against canned data. The JSON returned by each tool matches the real server's response shape field-for-field, including the <insecure-content> boundary tags that wrap user-controlled text (descriptions, notes, comments) so an LLM treats them as untrusted data rather than instructions. Nothing connects to a live Redmine; the point is to show the agent's tool loop, not to be a hosted service.

Install

redmine-mcp-server is MIT-licensed and published on PyPI. Install with pip install redmine-mcp-server, then point it at your Redmine URL with an API key or OAuth. The source is on GitHub and the package on PyPI. For the story behind it, see the blog post on linking a legacy system to a modern AI agent.

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