MCP Server: MCP Integration Tool by Trunk.io for AI Apps to Access CI Autopilot

MCP Server

The MCP server provided by Trunk.io enables AI applications to access the CI Autopilot feature, including obtaining root cause analysis and configuring test uploads.

Developer tools Artificial intelligence chatbots #CI/CD automation #AI development tools #MCP protocol #IDE integration

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update time : 2025-12-29

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What is the Trunk.io MCP Server?

The Trunk.io MCP Server is a service based on the Model Context Protocol (MCP). It allows your favorite AI applications (such as Claude Code, Cursor, etc.) to connect to Trunk.io's CI Autopilot feature. Simply put, it acts like a bridge, enabling the AI assistant to help you analyze the reasons for CI/CD build failures and guide you on how to set up test result uploads.

How to use the Trunk.io MCP Server?

It's very easy to use! You only need to make a one - time configuration in the AI application you are using (such as Cursor IDE, Claude Code CLI, etc.) and tell it the address of the Trunk MCP server. After the configuration is completed, you can directly ask the assistant to help you analyze build problems or get configuration suggestions in the AI conversation without leaving your development environment.

Applicable scenarios

When your continuous integration (CI) pipeline build fails, you can let the AI assistant quickly obtain the root cause of the failure and repair suggestions through this MCP server. Or, when you need to configure test result uploads to Trunk for your project, the AI assistant can generate a detailed configuration plan for you.

Main features

Get root cause analysis

The AI assistant can call this tool to obtain a root cause analysis report of CI build failures for you and provide specific repair suggestions to help you quickly locate and solve problems.

Generate a test upload configuration plan

This is an experimental feature. The AI assistant can call this tool to generate a detailed, step - by - step plan based on your project situation to guide you on how to upload test results to the Trunk platform.

Secure OAuth 2.0 authorization

The server uses the standard OAuth 2.0 and OpenID Connect protocols for authorization to ensure a secure and reliable connection and protect your data and access rights.

Advantages

Seamless integration: Use it directly in your familiar IDE or AI application without switching tools.

Improve efficiency: The AI assistant can quickly obtain professional analysis, saving you the time of manually troubleshooting CI issues.

Easy to configure: Just configure the server address once in the supported AI application and you can start using it.

Secure and reliable: Use the industry - standard OAuth 2.0 protocol for authentication and authorization.

Limitations

Limited application support: Currently only supports Cursor, Claude Code, GitHub Copilot, and Gemini CLI. Windsurf and Gemini Code Assist are not supported yet.

Function scope: Currently mainly provides two types of tools for CI issue analysis and test upload configuration.

Network - dependent: You need to be able to access the Trunk.io MCP server endpoint.

How to use

Select and configure your AI application

According to the AI application you are using, refer to the corresponding configuration guide in the Trunk official documentation for settings. You need to add the MCP server address (https://mcp.trunk.io/mcp) to the application's configuration.

Complete authorization

When connecting for the first time, the system will guide you through the OAuth 2.0 authorization process to securely connect your Trunk account.

Start a conversation

After the configuration is completed, you can directly ask the assistant to use Trunk's tools to help you in the conversation window of the AI application. For example, ask about the reason for the build failure.

Usage examples

Example 1: Quickly diagnose a failed CI build

After developer Xiao Zhang submitted his code, the CI pipeline showed a build failure. He didn't want to spend time manually checking the long logs. He directly asked the AI assistant in Cursor IDE: 'Why did the latest CI build fail?' The AI assistant called the tool through the MCP server and obtained a clear root cause analysis (e.g., 'The test failed due to a dependency library version conflict') and specific repair steps.

Example 2: Configure test reports for a new project

Engineer Xiao Li is responsible for a new project that needs to upload the results of unit tests and integration tests to Trunk for quality tracking. He is not familiar with the specific configuration process. He requested help in Claude Code CLI: 'I need to configure test uploads to Trunk for my Python project.' The AI assistant generated a customized configuration plan through the MCP server.