How do I use trac-mcp-server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@trac-mcp-server create a ticket for bug fix in login module" 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.

trac-mcp-server

by nerpatech

Overview Schema Related Servers Score Discussions

Python

Remote

trac-mcp-server

Standalone MCP server that gives AI agents full access to Trac project management -- tickets, wiki, milestones, and search -- via the Model Context Protocol.

Quick Start

pip install .

Set your Trac connection:

export TRAC_URL="https://trac.example.com"
export TRAC_USERNAME="your-username"
export TRAC_PASSWORD="your-password"

Run the server:

trac-mcp-server

Configuration

Configuration via environment variables, .env file, or YAML config file (.trac_mcp/config.yaml):

Variable	Required	Default	Description
`TRAC_URL`	Yes	--	Trac instance URL
`TRAC_USERNAME`	Yes	--	Trac username
`TRAC_PASSWORD`	Yes	--	Trac password
`TRAC_INSECURE`	No	`false`	Skip SSL verification (development only)
`TRAC_DEBUG`	No	`false`	Enable debug logging
`TRAC_MAX_PARALLEL_REQUESTS`	No	`5`	Max parallel XML-RPC requests
`TRAC_MAX_BATCH_SIZE`	No	`500`	Max items per batch operation (1-10000)

For YAML config file format and advanced options, see Configuration Reference.

MCP Client Integration

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "trac": {
      "command": "trac-mcp-server",
      "env": {
        "TRAC_URL": "https://trac.example.com",
        "TRAC_USERNAME": "your-username",
        "TRAC_PASSWORD": "your-password"
      }
    }
  }
}

Claude Code

claude mcp add trac -e TRAC_URL=https://trac.example.com \
  -e TRAC_USERNAME=your-username \
  -e TRAC_PASSWORD=your-password \
  -- trac-mcp-server

Other MCP Clients

Any MCP client that supports stdio transport can launch trac-mcp-server as a subprocess. Pass Trac credentials via environment variables.

Available Tools (27)

Tickets (11)

Tool	Description
`ticket_search`	Search tickets with Trac query language
`ticket_get`	Get ticket details by ID
`ticket_create`	Create new tickets
`ticket_update`	Update existing tickets
`ticket_delete`	Delete tickets
`ticket_changelog`	Get ticket change history
`ticket_fields`	List available ticket fields
`ticket_actions`	Get available ticket actions
`ticket_batch_create`	Create multiple tickets in one batch
`ticket_batch_delete`	Delete multiple tickets in one batch
`ticket_batch_update`	Update multiple tickets in one batch

Wiki (6)

Tool	Description
`wiki_get`	Get wiki page content (with Markdown conversion)
`wiki_search`	Search wiki pages
`wiki_create`	Create new wiki pages
`wiki_update`	Update existing wiki pages
`wiki_delete`	Delete wiki pages
`wiki_recent_changes`	List recent wiki changes

Wiki Files (3)

Tool	Description
`wiki_file_push`	Push local file to wiki (auto format conversion)
`wiki_file_pull`	Pull wiki page to local file
`wiki_file_detect_format`	Detect content format (Markdown/TracWiki)

Milestones (5)

Tool	Description
`milestone_list`	List all milestones
`milestone_get`	Get milestone details
`milestone_create`	Create new milestones
`milestone_update`	Update existing milestones
`milestone_delete`	Delete milestones

System (2)

Tool	Description
`ping`	Test connectivity and return API version
`get_server_time`	Get Trac server time

Development

pip install -e ".[dev]"
pytest tests/ -v

Project Structure

src/trac_mcp_server/
  config.py       # Environment variable configuration
  core/           # Trac XML-RPC client, async utilities
  mcp/            # MCP server, tools, resources
  converters/     # Markdown <-> TracWiki conversion
  detection/      # Content format detection

Documentation

See docs/reference/overview.md for detailed tool reference, configuration, and troubleshooting.

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Resources

GitHub Repository

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