# TestRail MCP Server

> Use this tool when you need to integrate AI assistants with TestRail for streamlined testing workflows, enabling them to browse projects, create test cases, and record results through natural-language conversations. It solves problems of manual test case management and validation, providing strongly-typed tool schemas and custom field validation for accurate AI-generated requests. Ideal for use cases where AI-driven testing automation and efficient collaboration are crucial.

Canonical page: https://skillsregistry.net/skills/uarlouski-testrail-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/uarlouski-testrail-mcp-server

## Description

AI-native Model Context Protocol (MCP) server for TestRail. Lets Claude, Cursor, Windsurf, and other AI assistants browse projects, create and update test cases, kick off test runs, and record results through natural-language conversation — with strongly-typed tool schemas and per-project custom field validation that helps LLMs generate valid TestRail requests on the first try.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/omzikhhvqa)
- **Repository:** <https://github.com/uarlouski/testrail-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "uarlouski-testrail-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/uarlouski-testrail-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/uarlouski-testrail-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt