developer-tools

Trunk

trunk-io

by trunk-io

Trunk CI Autopilot: automatically detect and fix failing tests to keep your builds green and accelerate delivery.

CI Autopilot tools for fixing failing tests

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Automated test failure diagnosisStreamable HTTP interface

best for

  • / Development teams with flaky test suites
  • / CI/CD pipelines with frequent test failures
  • / Developers spending too much time debugging tests

capabilities

  • / Analyze failing test outputs
  • / Generate fixes for broken tests
  • / Identify root causes of test failures
  • / Suggest code changes to resolve issues
  • / Monitor CI pipeline health

what it does

Automatically analyzes and fixes failing tests in your CI pipeline. Helps developers resolve test failures without manual debugging.

about

Trunk is an official MCP server published by trunk-io that provides AI assistants with tools and capabilities via the Model Context Protocol. Trunk CI Autopilot: automatically detect and fix failing tests to keep your builds green and accelerate delivery. It is categorized under developer tools.

how to install

You can install Trunk 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 supports remote connections over HTTP, so no local installation is required.

license

MIT

Trunk is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

[![Trunk.io](https://github.com/user-attachments/assets/c98a90ee-439b-4a9c-bb9a-69dc0e7e2c7e)](https://trunk.io) [![docs](https://img.shields.io/badge/-docs-darkgreen?logo=readthedocs&logoColor=ffffff)][docs] [![vscode](https://img.shields.io/visual-studio-marketplace/i/trunk.io?color=0078d7&label=vscode&logo=visualstudiocode)][vscode] [![slack](https://img.shields.io/badge/-slack-611f69?logo=slack)][slack] [![openssf](https://api.securityscorecards.dev/projects/github.com/trunk-io/trunk-action/badge)](https://api.securityscorecards.dev/projects/github.com/trunk-io/trunk-action) # Trunk.io MCP Server Leverage the power of Trunk Flaky Tests from your IDE, or the AI application of your choosing. ## Use MCP Server Trunk Flaky Tests comes with a [Model Context Protocol (MCP)](https://modelcontextprotocol.io/docs/getting-started/intro) server. AI applications like Claude Code or Cursor can use MCP servers to connect to data sources, tools, and workflows — enabling them to access key information and perform tasks. ### Supported AI Applications | Application | Supported | Guide | Plugin | | ---------------------------------------------------------------------------------------------------- | --------- | ------------------------------------------------------------------------------------------------- | --------------------------------------------------------------- | | [Cursor](https://docs.trunk.io/flaky-tests/use-mcp-server/configuration/cursor-ide) | Yes | [Setup guide](https://docs.trunk.io/flaky-tests/use-mcp-server/configuration/cursor-ide) | [Cursor plugin](https://github.com/trunk-io/cursor-plugin) | | [Claude Code](https://docs.trunk.io/flaky-tests/use-mcp-server/configuration/claude-code-cli) | Yes | [Setup guide](https://docs.trunk.io/flaky-tests/use-mcp-server/configuration/claude-code-cli) | [Claude Code plugin](https://github.com/trunk-io/claude-code-plugin) | | [GitHub Copilot](https://docs.trunk.io/flaky-tests/use-mcp-server/configuration/github-copilot-ide) | Yes | [Setup guide](https://docs.trunk.io/flaky-tests/use-mcp-server/configuration/github-copilot-ide) | | | [Gemini CLI](https://docs.trunk.io/flaky-tests/use-mcp-server/configuration/gemini-cli) | Yes | [Setup guide](https://docs.trunk.io/flaky-tests/use-mcp-server/configuration/gemini-cli) | | > [!NOTE] > Gemini Code Assist and Windsurf are not supported due to their limited support for MCP servers. ## Quick Start ### Cursor Add to `.cursor/mcp.json`: ```json { "mcpServers": { "trunk": { "url": "https://mcp.trunk.io/mcp" } } } ``` ### Claude Code ```bash claude mcp add trunk --transport streamable-http https://mcp.trunk.io/mcp ``` ### GitHub Copilot Add to `.vscode/mcp.json`: ```json { "servers": { "trunk": { "type": "http", "url": "https://mcp.trunk.io/mcp" } } } ``` ### Gemini CLI Add to `~/.gemini/settings.json`: ```json { "mcpServers": { "trunk": { "httpUrl": "https://mcp.trunk.io/mcp" } } } ``` ## API The MCP server is available at `https://mcp.trunk.io/mcp` and exposes the following tools: | Tool | Description | | ----------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------- | | [`fix-flaky-test`](https://docs.trunk.io/flaky-tests/use-mcp-server/mcp-tool-reference/get-root-cause-analysis) | Retrieve root cause analysis and fix suggestions for flaky tests | | [`setup-trunk-uploads`](https://docs.trunk.io/flaky-tests/use-mcp-server/mcp-tool-reference/set-up-test-uploads) | Generate a setup plan to upload test results to Trunk | ## Authorization The Trunk MCP server supports the **OAuth 2.0 + OpenID Connect** standard for MCP authorization. When connecting from a supported client, you will be prompted to authenticate via your Trunk account. --- **Made with love by the [Trunk.io](https://trunk.io) team** [slack]: https://slack.trunk.io [docs]: https://docs.trunk.io [vscode]: https://marketplace.visualstudio.com/items?itemName=Trunk.io

FAQ

What is the Trunk MCP server?
Trunk 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 Trunk?
This profile displays 42 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.742 reviews
  • Sophia Sethi· Dec 24, 2024

    Trunk is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Maya Srinivasan· Dec 20, 2024

    Trunk is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Ganesh Mohane· Dec 8, 2024

    We evaluated Trunk against two servers with overlapping tools; this profile had the clearer scope statement.

  • Sakshi Patil· Nov 27, 2024

    Trunk has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Diya Torres· Nov 15, 2024

    Useful MCP listing: Trunk is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Charlotte Park· Nov 11, 2024

    According to our notes, Trunk benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Hana Tandon· Nov 3, 2024

    Strong directory entry: Trunk surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Maya White· Oct 22, 2024

    I recommend Trunk for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Chaitanya Patil· Oct 18, 2024

    According to our notes, Trunk benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Ira Mehta· Oct 6, 2024

    Trunk reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

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