Yellhorn MCP
@msnidal
About Yellhorn MCP
Yellhorn offers MCP tools to publish detailed workplans as GitHub issues with entire-codebase reasoning and to review diffs against them
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"yellhorn-mcp": {
"command": "uv",
"args": [
"sync",
"--group",
"dev"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Yellhorn MCP?
Yellhorn MCP is a Model Context Protocol server that creates detailed workplans for implementing tasks or features. It uses large AI models (e.g., Gemini 2.5 Pro, GPT‑5, o3, Grok‑4) with full codebase context, URL access, and optional web search. The server is designed for coding agents like Claude Code to define work, and later to review the output against the original requirements.
How to use Yellhorn MCP?
Install via uv sync --group dev or uv pip install yellhorn-mcp. Set environment variables GEMINI_API_KEY, OPENAI_API_KEY, XAI_API_KEY, REPO_PATH, and optionally YELLHORN_MCP_MODEL and YELLHORN_MCP_SEARCH. The GitHub CLI (gh) must be installed and authenticated. Configure the server in your MCP client (Codex CLI, VSCode/Cursor, or Claude Code) using a config.toml or mcp.json file with command uv run yellhorn-mcp.
Key features of Yellhorn MCP
- Creates detailed workplans posted as GitHub issues
- Judges code diffs against the original workplan
- Seamless GitHub integration with labeled issues and sub‑issues
.yellhornignorefile to exclude files from AI context- MCP resources for listing and retrieving workplans
- Google Search Grounding enabled by default for Gemini models
Use cases of Yellhorn MCP
- Defining implementation tasks for coding agents (e.g., Claude Code)
- Reviewing code agent output against specified requirements
- Generating workplans with full codebase awareness
- Iteratively revising workplans based on feedback
FAQ from Yellhorn MCP
What models does Yellhorn MCP support?
It supports Gemini (2.5‑pro, 2.5‑flash, 2.5‑flash‑lite), OpenAI (GPT‑4o, GPT‑4o‑mini, o4‑mini, o3, GPT‑4.1, GPT‑5 series), and xAI Grok (Grok‑4, Grok‑4 Fast) models. Deep Research models (o3‑deep‑research, o4‑mini‑deep‑research, GPT‑5) enable web search and code interpreter tools.
How do I exclude files from AI context?
Create a .yellhornignore file in your repository, similar to .gitignore. The server also provides the curate_context tool to generate a .yellhorncontext whitelist that further reduces token usage.
What are the prerequisites for using Yellhorn MCP?
You need API keys for the models you plan to use (Gemini, OpenAI, or xAI), the GitHub CLI (gh) installed and authenticated, and a Python environment managed by uv. The repository to analyze must be accessible via REPO_PATH.
Can I disable web search in workplans?
Yes. Set the environment variable YELLHORN_MCP_SEARCH to "off" (default is "on" for Gemini models). You can also pass disable_search_grounding: true to individual tool calls.
How does workplan judgment work?
The judge_workplan tool compares two git refs (base and head) against a workplan stored in a GitHub issue. It creates a sub‑issue, then asynchronously evaluates the diff with full codebase context and posts detailed feedback.
Frequently asked questions
What models does Yellhorn MCP support?
It supports Gemini (2.5‑pro, 2.5‑flash, 2.5‑flash‑lite), OpenAI (GPT‑4o, GPT‑4o‑mini, o4‑mini, o3, GPT‑4.1, GPT‑5 series), and xAI Grok (Grok‑4, Grok‑4 Fast) models. Deep Research models (o3‑deep‑research, o4‑mini‑deep‑research, GPT‑5) enable web search and code interpreter tools.
How do I exclude files from AI context?
Create a `.yellhornignore` file in your repository, similar to `.gitignore`. The server also provides the `curate_context` tool to generate a `.yellhorncontext` whitelist that further reduces token usage.
What are the prerequisites for using Yellhorn MCP?
You need API keys for the models you plan to use (Gemini, OpenAI, or xAI), the GitHub CLI (`gh`) installed and authenticated, and a Python environment managed by `uv`. The repository to analyze must be accessible via `REPO_PATH`.
Can I disable web search in workplans?
Yes. Set the environment variable `YELLHORN_MCP_SEARCH` to `"off"` (default is `"on"` for Gemini models). You can also pass `disable_search_grounding: true` to individual tool calls.
How does workplan judgment work?
The `judge_workplan` tool compares two git refs (base and head) against a workplan stored in a GitHub issue. It creates a sub‑issue, then asynchronously evaluates the diff with full codebase context and posts detailed feedback.
Basic information
More Version Control MCP servers
GitLab MCP Server
yoda-digitalProduction-grade GitLab MCP server with 86 tools — full GitLab control from any AI agent (Claude, Cursor, Zed).

GitLab
modelcontextprotocolModel Context Protocol Servers
AIO-MCP Server
athapong🚀 All-in-one MCP server with AI search, RAG, and multi-service integrations (GitLab/Jira/Confluence/YouTube) for AI-enhanced development workflows. Folk from https://github.com/nguyenvanduocit/all-in-one-model-context-protocol
GitHub Actions 工作流使用说明
HenryHaosonYuque mcp server
Atlassian Jira MCP Server
aashariNode.js/TypeScript MCP server for Atlassian Jira. Equips AI systems (LLMs) with tools to list/get projects, search/get issues (using JQL/ID), and view dev info (commits, PRs). Connects AI capabilities directly into Jira project management and issue tracking workflows.
Comments