TestRail▌

by sker65
Bridge TestRail with AI tools for smarter, streamlined software testing workflows. Leverage artificial intelligence in s
Bridges TestRail's test management platform with AI tools, enabling interaction with projects, test cases, runs, results, and datasets for streamlined software testing workflows.
best for
- / QA engineers automating test management workflows
- / Development teams integrating testing with AI assistants
- / Test managers analyzing results across projects
capabilities
- / Query TestRail projects and test cases
- / Access test runs and execution results
- / Manage test datasets programmatically
- / Authenticate with TestRail API
- / Browse project hierarchies and test structures
what it does
Connects AI tools directly to TestRail's test management platform, allowing you to query and manage test cases, runs, results, and projects through natural language.
about
TestRail is a community-built MCP server published by sker65 that provides AI assistants with tools and capabilities via the Model Context Protocol. Bridge TestRail with AI tools for smarter, streamlined software testing workflows. Leverage artificial intelligence in s It is categorized under developer tools, productivity.
how to install
You can install TestRail in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
TestRail is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
TestRail MCP Server
A Model Context Protocol (MCP) server for TestRail that allows interaction with TestRail's core entities through a standardized protocol.
Features
- Authentication with TestRail API
- Access to TestRail entities:
- Projects
- Cases
- Runs
- Results
- Datasets
- Full support for the Model Context Protocol
- Compatible with any MCP client (Claude Desktop, Cursor, Windsurf, etc.)
See it in action together with Octomind MCP
Installation
Installing via Smithery
To install testrail-mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @sker65/testrail-mcp --client claude
Manual Installation
-
Clone this repository:
git clone https://github.com/yourusername/testrail-mcp.git cd testrail-mcp -
Create and activate a virtual environment:
python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate -
Install dependencies:
pip install -e .
Configuration
The TestRail MCP server requires specific environment variables to authenticate with your TestRail instance. These must be set before running the server.
-
Create a
.envfile in the root directory of the project:TESTRAIL_URL=https://your-instance.testrail.io TESTRAIL_USERNAME=your-email@example.com TESTRAIL_API_KEY=your-api-keyImportant Notes:
TESTRAIL_URLshould be the full URL to your TestRail instance (e.g.,https://example.testrail.io)TESTRAIL_USERNAMEis your TestRail email address used for loginTESTRAIL_API_KEYis your TestRail API key (not your password)- To generate an API key, log in to TestRail, go to "My Settings" > "API Keys" and create a new key
-
Verify that the configuration is loaded correctly:
uvx testrail-mcp --configThis will display your TestRail configuration information, including your URL, username, and the first few characters of your API key for verification.
If you're using this server with a client like Claude Desktop or Cursor, make sure the environment variables are accessible to the process running the server. You may need to set these variables in your system environment or ensure they're loaded from the .env file.
Usage
Running the Server
The server can be run directly using the installed script:
uvx testrail-mcp
This will start the MCP server in stdio mode, which can be used with MCP clients that support stdio communication.
Using with MCP Clients
Claude Desktop
In Claude Desktop, add a new server with the following configuration:
{
"mcpServers": {
"testrail": {
"command": "uvx",
"args": [
"testrail-mcp"
],
"env": {
"TESTRAIL_URL": "https://your-instance.testrail.io",
"TESTRAIL_USERNAME": "your-email@example.com",
"TESTRAIL_API_KEY": "your-api-key"
}
}
}
}
Cursor
In Cursor, add a new custom tool with the following configuration:
{
"name": "TestRail MCP",
"command": "uvx",
"args": [
"testrail-mcp"
],
"env": {
"TESTRAIL_URL": "https://your-instance.testrail.io",
"TESTRAIL_USERNAME": "your-email@example.com",
"TESTRAIL_API_KEY": "your-api-key"
}
}
Windsurf
In Windsurf, add a new tool with the following configuration:
{
"name": "TestRail MCP",
"command": "uvx",
"args": [
"testrail-mcp"
],
"env": {
"TESTRAIL_URL": "https://your-instance.testrail.io",
"TESTRAIL_USERNAME": "your-email@example.com",
"TESTRAIL_API_KEY": "your-api-key"
}
}
Testing with MCP Inspector
For testing and debugging, you can use the MCP Inspector:
npx @modelcontextprotocol/inspector \
-e TESTRAIL_URL=<your-url> \
-e TESTRAIL_USERNAME=<your-username> \
-e TESTRAIL_API_KEY=<your-api-key> \
uvx testrail-mcp
This will open a web interface where you can explore and test all the available tools and resources.
Development
This server is built using:
- FastMCP - A Python framework for building MCP servers
- Requests - For HTTP communication with TestRail API
- python-dotenv - For environment variable management
License
MIT
FAQ
- What is the TestRail MCP server?
- TestRail is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for TestRail?
- This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Ratings
4.5★★★★★10 reviews- ★★★★★Shikha Mishra· Oct 10, 2024
TestRail is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Piyush G· Sep 9, 2024
We evaluated TestRail against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: TestRail is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Sakshi Patil· Jul 7, 2024
TestRail reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ganesh Mohane· Jun 6, 2024
I recommend TestRail for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: TestRail surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Dhruvi Jain· Apr 4, 2024
TestRail has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Rahul Santra· Mar 3, 2024
According to our notes, TestRail benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Pratham Ware· Feb 2, 2024
We wired TestRail into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Yash Thakker· Jan 1, 2024
TestRail is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
