TestRail MCP Server

TestRail MCP Server

Connect your AI coding assistant to TestRail to manage test cases, runs, results, and more directly from VS Code, Cursor, Claude Desktop, or Claude Code.

Category
Visit Server

README

TestRail MCP Server

Tests Python 3.11 | 3.12 | 3.13 PyPI - Version PyPI - Downloads License: MIT

Connect your AI coding assistant to TestRail — manage test cases, runs, results, and more directly from VS Code, Cursor, Claude Desktop, or Claude Code. Built on the Model Context Protocol and powered by testrail_api_module.

Features

  • Dynamic tool discovery — endpoints are introspected from testrail_api_module at startup, so new API coverage is picked up automatically
  • LLM-friendly — instead of registering hundreds of tools, provides a category-based discovery pattern so models can explore available operations without being overwhelmed

Requirements

  • Python 3.11+
  • uv

Installation

Step 1 — Install tram-mcp once

uv tool install tram-mcp

This puts a tram-mcp binary on your PATH (typically ~/.local/bin/tram-mcp on macOS/Linux, %APPDATA%\Python\Scripts\tram-mcp.exe on Windows).

tram-mcp then auto-updates itself: on launch (at most once per day) it spawns a detached uv tool upgrade tram-mcp in the background. The current process keeps running on the existing binary; the upgrade lands on the next launch. Set TRAM_MCP_NO_AUTO_UPDATE=1 to disable, or run uv tool upgrade tram-mcp manually anytime.

Why this and not uvx tram-mcp? uvx re-resolves and re-extracts wheels on every launch. On Windows this races with Defender / OneDrive scanning the uv cache and intermittently fails with Access is denied. (os error -2147024891) — the server starts, then exits before it can respond. Even on a healthy machine, a cold uvx cache costs ~4 s+ and can exceed an MCP client's startup timeout. Installing once removes both problems.

Step 2 — Configure your MCP client

Claude Desktop

Add to your Claude Desktop config file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "testrail": {
      "command": "tram-mcp",
      "env": {
        "TESTRAIL_URL": "https://yourinstance.testrail.io",
        "TESTRAIL_USERNAME": "your-email@example.com",
        "TESTRAIL_API_KEY": "your-api-key"
      }
    }
  }
}

Claude Code

claude mcp add testrail \
  -e TESTRAIL_URL=https://yourinstance.testrail.io \
  -e TESTRAIL_USERNAME=your-email@example.com \
  -e TESTRAIL_API_KEY=your-api-key \
  -- tram-mcp

VS Code / VS Code Insiders

Create .vscode/mcp.json in your project (or add to your User Settings):

{
  "servers": {
    "testrail": {
      "type": "stdio",
      "command": "tram-mcp",
      "env": {
        "TESTRAIL_URL": "",
        "TESTRAIL_USERNAME": "",
        "TESTRAIL_API_KEY": ""
      }
    }
  }
}

VS Code supports ${input:variableName} placeholders to prompt for values at startup.

Cursor

Create .cursor/mcp.json in your project (or ~/.cursor/mcp.json globally):

{
  "mcpServers": {
    "testrail": {
      "command": "tram-mcp",
      "env": {
        "TESTRAIL_URL": "https://yourinstance.testrail.io",
        "TESTRAIL_USERNAME": "your-email@example.com",
        "TESTRAIL_API_KEY": "your-api-key"
      }
    }
  }
}

Alternative — no-install via uvx

If you prefer not to maintain a separate install, you can use uvx tram-mcp as the command (with "args": ["tram-mcp"]) — Cursor / VS Code / etc. style. This re-resolves on each launch, so a cold cache pays a noticeable ~4 s cost that can intermittently exceed MCP client startup timeouts. The launch-time auto-update (see above) also no-ops in this mode — uvx already pulls fresh on each invocation.

Not recommended on Windows. uvx's per-launch wheel extraction races Windows Defender real-time scanning and OneDrive sync over the uv cache, producing intermittent Failed to install: <wheel>. Caused by: Access is denied. (os error -2147024891) errors and "server failed to start" behavior that retries fix. Use the uv tool install path above instead.

Configuration

The server requires TestRail credentials via environment variables:

Variable Required Description
TESTRAIL_URL Yes Your TestRail instance URL (e.g. https://example.testrail.io)
TESTRAIL_USERNAME Yes TestRail username or email
TESTRAIL_API_KEY Yes* TestRail API key
TESTRAIL_PASSWORD Yes* TestRail password (alternative to API key)

*Either TESTRAIL_API_KEY or TESTRAIL_PASSWORD must be set. API key is recommended.

Development

# Install dependencies
uv sync

# Run the server locally
uv run tram_mcp

# Run tests
uv run pytest

# Run a single test
uv run pytest path/to/test.py::test_name -v

Releasing

Merging a PR to main automatically tags the version and publishes to PyPI. You must bump the version before merging:

uv version 0.6.0  # update version in pyproject.toml

Also bump manifest.json's version to match — both files must agree, and the .mcpb upload is rejected when the version isn't incremented. If you forget to bump, the PyPI publish is skipped (the existing version tag already exists on PyPI).

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured