Redmine MCP Server
Enables AI applications to interact with Redmine project management systems for issue tracking, time logging, and project management through natural language.
README
Redmine MCP Server
A Model Context Protocol (MCP) server for integrating with Redmine project management systems. This server provides AI applications with the ability to interact with Redmine instances for project management, issue tracking, and time logging.
Features
Tools
get_issues- Retrieve issues with optional filtering by project, status, assigneeget_projects- List available Redmine projectsget_project_memberships- Get users and groups assigned to a project with their rolescreate_issue- Create new issues in Redmine projectsget_time_entries- Retrieve time entries with filtering optionslog_time- Log time spent on issues or projects
Resources
- redmine://projects - List of all accessible projects
- redmine://issues/recent - Recently updated issues
- redmine://time_entries/recent - Recently logged time entries
Prompts
- issue_summary - Generate comprehensive project issue summaries
- time_report - Create detailed time tracking reports
Setup
Prerequisites
- Node.js 22+
- Access to a Redmine instance with API key
- Redmine REST API enabled
Environment Variables
Set the following environment variables:
export REDMINE_URL="https://your-redmine-instance.com"
export REDMINE_API_KEY="your_api_key_here"
Installation
- Clone or download this repository
- Install dependencies:
npm install - Build the server:
npm run build
Usage with MCP Clients
VsCode
Clone this repository and create the file .vscode/mcp.json with following
contents:
{
"servers": {
"redmine-mcp-server": {
"type": "stdio",
"command": "node",
"args": ["build/src/index.js"],
"env": {
"REDMINE_URL": "your URL here",
"REDMINE_API_KEY": "your API key here"
}
}
}
}
After adding the file, restart VsCode and open the Chat window. Redmine MCP
Server should be available and running in MCP servers list (Ctrl-P, then type
"MCP list servers"):

Documentation
API documentation is automatically generated from JSDoc comments and deployed to GitHub Pages:
To generate documentation locally:
npm run docs
The generated documentation will be available in the docs/ directory.
Development
Building
npm run build
Linting
npm run lint
npm run format
Testing
This project uses Vitest as its testing framework, providing fast test execution, watch mode, and comprehensive coverage reports.
Running Tests
# Run all tests
npm test
# Run tests once and exit
npm run test:run
# Run only e2e tests
npm run test:e2e
# Run tests with UI
npm run test:ui
# Run tests with coverage
npm run test:coverage
Coverage Reporting
Code coverage is automatically collected and reported in the CI pipeline using Vitest's built-in coverage support with the V8 provider. Coverage reports are:
- Generated for every test run in CI
- Uploaded as workflow artifacts (available for 30 days)
- Displayed in the GitHub Actions workflow summary
- Stored in the
coverage/directory locally
To generate coverage locally:
npm run test:coverage
Coverage reports include:
- HTML report: Open
coverage/index.htmlin your browser for detailed line-by-line coverage - JSON summary:
coverage/coverage-summary.jsoncontains overall metrics - Text output: Coverage percentages displayed in the terminal
The coverage configuration excludes test files, configuration files, and build artifacts to focus on source code coverage.
Test Structure
test/e2e/- End-to-end tests using Docker and Playwright
Writing Tests
Tests use Vitest's describe, it, and expect API:
import { describe, it, expect } from "vitest";
describe("My Feature", () => {
it("should work correctly", () => {
expect(1 + 1).toBe(2);
});
});
Testing with MCP Inspector
npx @modelcontextprotocol/inspector node build/src/index.js
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。