The Taiga MCP Bridge provides seamless integration between the Taiga project management platform and AI tools using the Model Context Protocol (MCP). This bridge allows AI systems to create and manage Taiga resources like projects, epics, user stories, and tasks while maintaining contextual awareness about project state.
# Clone the repository
git clone https://github.com/your-org/pyTaigaMCP.git
cd pyTaigaMCP
# Install dependencies
./install.sh
If you prefer to install manually:
# Production dependencies only
uv pip install -e .
# With development dependencies
uv pip install -e ".[dev]"
The bridge can be configured through environment variables or a .env file:
| Environment Variable | Description | Default |
|---|---|---|
| TAIGA_API_URL | Base URL for the Taiga API | http://localhost:9000 |
| SESSION_EXPIRY | Session expiration time in seconds | 28800 (8 hours) |
| TAIGA_TRANSPORT | Transport mode (stdio or sse) | stdio |
| REQUEST_TIMEOUT | API request timeout in seconds | 30 |
| MAX_CONNECTIONS | Maximum number of HTTP connections | 10 |
| MAX_KEEPALIVE_CONNECTIONS | Max keepalive connections | 5 |
| RATE_LIMIT_REQUESTS | Max requests per minute | 100 |
| LOG_LEVEL | Logging level | INFO |
| LOG_FILE | Path to log file | taiga_mcp.log |
Create a .env file in the project root to set these values:
TAIGA_API_URL=https://api.taiga.io/api/v1/
TAIGA_TRANSPORT=sse
LOG_LEVEL=DEBUG
Paste the following json in your Claude App's or Cursor's mcp settings section:
{
"mcpServers": {
"taigaApi": {
"command": "uv",
"args": [
"--directory",
"<path to local pyTaigaMCP folder>",
"run",
"src/server.py"
],
"env": {
"TAIGA_TRANSPORT": "<stdio|sse>",
"TAIGA_API_URL": "<Taiga API Url (ex: http://localhost:9000)",
"TAIGA_USERNAME": "<taiga username>",
"TAIGA_PASSWORD": "<taiga password>"
}
}
}
}
Start the MCP server with:
# Default stdio transport
./run.sh
# For SSE transport
./run.sh --sse
Or manually:
# For stdio transport (default)
uv run python src/server.py
# For SSE transport
uv run python src/server.py --sse
The server supports two transport modes:
You can set the transport mode in several ways:
This MCP bridge uses a session-based authentication model:
Clients must first authenticate using the login tool:
session = client.call_tool("login", {
"username": "your_taiga_username",
"password": "your_taiga_password",
"host": "https://api.taiga.io" # Optional
})
# Save the session_id from the response
session_id = session["session_id"]
Include the session_id in every API call:
# For resources, include session_id in the URI
projects = client.get_resource(f"taiga://projects?session_id={session_id}")
# For project-specific resources
epics = client.get_resource(f"taiga://projects/123/epics?session_id={session_id}")
# For tools, include session_id as a parameter
new_project = client.call_tool("create_project", {
"session_id": session_id,
"name": "New Project",
"description": "Description"
})
You can check if your session is still valid:
status = client.call_tool("session_status", {"session_id": session_id})
# Returns information about session validity and remaining time
When finished, you can logout to terminate the session:
client.call_tool("logout", {"session_id": session_id})
The bridge provides comprehensive support for Taiga resources with complete CRUD operations:
To add this MCP server to Claude Code, run this command in your terminal:
claude mcp add-json "taigaApi" '{"command":"uv","args":["--directory","<path to local pyTaigaMCP folder>","run","src/server.py"],"env":{"TAIGA_TRANSPORT":"<stdio|sse>","TAIGA_API_URL":"<Taiga API Url (ex: http://localhost:9000)","TAIGA_USERNAME":"<taiga username>","TAIGA_PASSWORD":"<taiga password>"}}'See the official Claude Code MCP documentation for more details.
There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.
If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.
To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".
When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:
{
"mcpServers": {
"taigaApi": {
"command": "uv",
"args": [
"--directory",
"<path to local pyTaigaMCP folder>",
"run",
"src/server.py"
],
"env": {
"TAIGA_TRANSPORT": "<stdio|sse>",
"TAIGA_API_URL": "<Taiga API Url (ex: http://localhost:9000)",
"TAIGA_USERNAME": "<taiga username>",
"TAIGA_PASSWORD": "<taiga password>"
}
}
}
}To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.
Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.
The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.
You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.
To add this MCP server to Claude Desktop:
1. Find your configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/Claude/claude_desktop_config.json2. Add this to your configuration file:
{
"mcpServers": {
"taigaApi": {
"command": "uv",
"args": [
"--directory",
"<path to local pyTaigaMCP folder>",
"run",
"src/server.py"
],
"env": {
"TAIGA_TRANSPORT": "<stdio|sse>",
"TAIGA_API_URL": "<Taiga API Url (ex: http://localhost:9000)",
"TAIGA_USERNAME": "<taiga username>",
"TAIGA_PASSWORD": "<taiga password>"
}
}
}
}3. Restart Claude Desktop for the changes to take effect