mantis-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mantis-mcpsearch for issues about database connection errors"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: MantisBT MCP Server
Quick Start
1. Install
git clone git@github.com:f-liva/mantis-mcp.git
cd mantis-mcp
npm install
npm run build2. 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 setupThis 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.jsonmacOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonLinux:
~/.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 |
| Yes | — | MantisBT REST API base URL |
| Yes | — | API token (from MantisBT → My Account → API Tokens) |
| No |
| SQLite database file path |
| No |
| Hugging Face model for embeddings |
| No |
| Issues fetched per batch during sync |
| No |
| Auto-sync when server starts |
| No |
|
|
Tools Reference
CRUD Tools (8)
Tool | Description | Key Parameters |
| List issues with filters |
|
| Get full issue details |
|
| Create a new issue |
|
| Update an existing issue |
|
| Add a note/comment |
|
| List all projects | — |
| Look up user by username |
|
| List project members |
|
Semantic Search Tools (3)
Tool | Description | Key Parameters |
| Natural language search across indexed issues/notes |
|
| Sync MantisBT data into vector index |
|
| 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 scoresKeep 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 resultsEmbeddings: 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
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