mantis-mcp
Enables natural language interaction with MantisBT issues and notes via CRUD operations and semantic search.
README
mantis-mcp
MCP (Model Context Protocol) server for MantisBT with CRUD operations and semantic search (RAG) over issues and notes.
Enables natural language queries like "have I ever discussed X with client Y?" across a large MantisBT database (10,000+ issues).
Features
- 8 CRUD tools — list/get/create/update issues, add notes, list projects and users
- 3 semantic search tools — natural language search across all issues and notes, with incremental sync
- Local embeddings — runs entirely offline using Transformers.js (no external API calls for search)
- Multilingual — uses
paraphrase-multilingual-MiniLM-L12-v2model (IT/EN/DE/FR/ES/...) - Incremental sync — only processes new/updated/deleted issues after the initial sync
Quick Start
1. Install
git clone git@github.com:f-liva/mantis-mcp.git
cd mantis-mcp
npm install
npm run build
2. Setup (automated)
Run the interactive setup script — it detects your platform (WSL, Windows, macOS, Linux), asks for your MantisBT credentials, tests the connection, and configures everything automatically:
./setup.sh setup
This will:
- Prompt for your MantisBT API URL and token
- Test the API connection
- Configure Claude Desktop (
claude_desktop_config.json) - Configure Claude Code (
.mcp.json) - Create the
.envfile
You can also pass parameters directly:
./setup.sh setup -u "https://mantis.example.com/api/rest" -k "your-api-token"
Or configure only one target:
./setup.sh setup -t desktop # only Claude Desktop
./setup.sh setup -t cli # only Claude Code
./setup.sh setup -t both # both (default)
3. Manual Configuration (alternative)
If you prefer to configure manually:
Claude Desktop
Edit your claude_desktop_config.json:
- Windows:
%APPDATA%\Claude\claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Linux:
~/.config/claude/claude_desktop_config.json
Windows (without WSL):
{
"mcpServers": {
"mantis": {
"command": "node",
"args": ["C:\\Users\\YOURUSERNAME\\mantis-mcp\\dist\\index.js"],
"env": {
"MANTIS_API_URL": "https://mantis.example.com/api/rest",
"MANTIS_API_KEY": "your-api-token"
}
}
}
}
Windows with WSL:
{
"mcpServers": {
"mantis": {
"command": "wsl",
"args": ["bash", "-c", "cd /home/YOURUSERNAME/mantis-mcp && node dist/index.js"],
"env": {
"MANTIS_API_URL": "https://mantis.example.com/api/rest",
"MANTIS_API_KEY": "your-api-token"
}
}
}
}
macOS / Linux:
{
"mcpServers": {
"mantis": {
"command": "node",
"args": ["/absolute/path/to/mantis-mcp/dist/index.js"],
"env": {
"MANTIS_API_URL": "https://mantis.example.com/api/rest",
"MANTIS_API_KEY": "your-api-token"
}
}
}
}
Claude Code (CLI)
Create a .mcp.json in any project directory:
{
"mcpServers": {
"mantis": {
"command": "node",
"args": ["/absolute/path/to/mantis-mcp/dist/index.js"],
"env": {
"MANTIS_API_URL": "https://mantis.example.com/api/rest",
"MANTIS_API_KEY": "your-api-token"
}
}
}
}
Configuration
| Variable | Required | Default | Description |
|---|---|---|---|
MANTIS_API_URL |
Yes | — | MantisBT REST API base URL |
MANTIS_API_KEY |
Yes | — | API token (from MantisBT → My Account → API Tokens) |
DB_PATH |
No | ./mantis-mcp.db |
SQLite database file path |
EMBEDDING_MODEL |
No | Xenova/paraphrase-multilingual-MiniLM-L12-v2 |
Hugging Face model for embeddings |
SYNC_BATCH_SIZE |
No | 50 |
Issues fetched per batch during sync |
SYNC_ON_STARTUP |
No | false |
Auto-sync when server starts |
LOG_LEVEL |
No | info |
error / warn / info / debug |
Tools Reference
CRUD Tools (8)
| Tool | Description | Key Parameters |
|---|---|---|
get_issues |
List issues with filters | page, page_size, project_id, filter_id |
get_issue_by_id |
Get full issue details | id |
create_issue |
Create a new issue | summary, description, project_id, category, priority |
update_issue |
Update an existing issue | id, summary, description, status, handler |
add_issue_note |
Add a note/comment | issue_id, text, view_state |
get_projects |
List all projects | — |
get_user |
Look up user by username | username |
get_users_by_project_id |
List project members | project_id |
Semantic Search Tools (3)
| Tool | Description | Key Parameters |
|---|---|---|
search |
Natural language search across indexed issues/notes | query, limit |
sync_index |
Sync MantisBT data into vector index | project_id (optional) |
sync_status |
Check index status and counts | — |
Search Workflow
- First time: Call
sync_indexto populate the vector database (may take several minutes for large databases) - Search: Use
searchwith natural language queries — results include similarity scores - Keep updated: Call
sync_indexperiodically — it performs incremental sync (only changed issues)
Architecture
Claude Desktop / Claude Code
│
│ stdio (JSON-RPC)
▼
mantis-mcp server
│
├── CRUD tools ──────► MantisBT REST API
│
└── Search tools
├── sync ──────► MantisBT REST API → Embeddings → SQLite + sqlite-vec
└── search ────► Embeddings → sqlite-vec KNN → Ranked results
- Embeddings: Generated locally with Transformers.js (~80MB model downloaded on first use)
- Vector storage: SQLite with sqlite-vec extension for fast cosine similarity search
- Sync: Compares
updated_attimestamps to detect changes, then re-embeds only modified issues
License
MIT
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。