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GitHub Issue MCP

Generates structured GitHub issues, checks duplicate candidates, and creates approved issues through MCP.

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Install GitHub Issue MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "github-issue-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "github-issue-mcp"
      ],
      "env": {
        "GITHUB_TOKEN": "YOUR_VALUE_HERE",
        "GITHUB_OWNER": "YOUR_VALUE_HERE",
        "GITHUB_REPO": "YOUR_VALUE_HERE",
        "GEMINI_API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— the server itself is confirmed live (we called its tools/list endpoint). The stdio install command is a separate, ongoing check.

Overview

GitHub Issue MCP MCP server turns issue descriptions into structured GitHub issues and checks open issues for likely duplicates. It connects to the GitHub REST API through an MCP stdio server and uses Google Gemini for issue generation and semantic duplicate analysis. The workflow separates candidate retrieval, analysis, issue drafting, approval, and GitHub creation. Reach for it when you want a human-controlled workflow for filing issues from natural-language bug reports.

Use cases

  • Generate structured bug reports from natural-language descriptions
  • Check proposed issues against existing open issues
  • Retrieve repository labels before drafting an issue
  • Create approved issues through a human-reviewed workflow

Key features

  • Structured issue generation with Google Gemini
  • Lexical duplicate candidate ranking
  • GitHub issue and label retrieval
  • Human approval before issue creation
  • Configurable Gemini retries and model
  • MCP stdio CLI and npm package

Tools5

What GitHub Issue MCP lets your agent do. Expand a tool for its parameters.

Verified live~754 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

8/8 checks healthy over the last 50d

What it can do

From the 5 tools this server returned when we ran it.

Read-only tools · 5
Network at startup3 connections
Files written at startupNone
Install scriptsNone
npm provenanceNot published
Package age70 days
Maintainers1

Observed 2026-10-22 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 9d ago via OSV.dev · github-issue-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

npm downloads171Package downloads in the last 30 days.
Last commit17d agoMost recent push to the default branch.
Tools exposed5Callable tools this server registers over MCP.
Directory activity2 viewsConfig copies, upvotes, and views on AllMCPs.

How GitHub Issue MCP works

What the GitHub Issue MCP MCP server does

GitHub Issue MCP MCP server supports a controlled workflow for managing issues in one configured GitHub repository. It can turn supplied bug information into a structured issue draft, retrieve open issues and repository labels, identify likely duplicate candidates, and create a new issue after approval.

The generation step accepts details such as a description, reproduction steps, expected and actual behavior, environment information, and additional context. It returns a proposed title, formatted body, and labels. The server also supports label retrieval so an application can inspect the labels available in the target repository.

How it works

The GitHub Issue MCP MCP server runs as an MCP process over standard input and output. GitHub operations use the GitHub REST API, while Google Gemini handles issue generation and the final semantic review of duplicate candidates.

Duplicate checking uses two stages. First, check_duplicate_issue retrieves open issues and applies inexpensive lexical ranking to produce a smaller candidate set. Those results are only possible matches, not proof of duplication. Gemini then performs the semantic comparison. Do not call list_github_issues separately for duplicate checking; use the dedicated duplicate tool.

The intended workflow keeps persistent writes outside autonomous model access. After duplicate analysis, an application can collect more details, generate a draft, show it to the user, and request approval. Only then should the client invoke create_github_issue. The tool is deliberately not available to the autonomous Gemini agent.

Setup and configuration

Install the published npm package with npm install github-issue-mcp, or launch the MCP CLI directly with npx -y github-issue-mcp. Configure an MCP-compatible client to start that command and communicate over stdio.

The server requires GITHUB_TOKEN, GITHUB_OWNER, GITHUB_REPO, and GEMINI_API_KEY. GITHUB_OWNER and GITHUB_REPO identify the repository used by the GitHub tools. Optional settings include GEMINI_MODEL, GEMINI_MAX_RETRIES, GEMINI_RETRY_BASE_DELAY, and DEBUG; the documented defaults are gemini-3.6-flash, 3, 1000 milliseconds, and false respectively.

Keep GitHub tokens and Gemini API keys out of source control and do not commit the .env file.

Tools and capabilities

  • generate_issue: Builds a structured issue from supplied issue information.
  • check_duplicate_issue: Ranks likely matches among existing open issues for later semantic review.
  • list_github_issues: Retrieves open issues and excludes pull requests.
  • list_github_labels: Retrieves labels from the configured repository.
  • create_github_issue: Creates the approved issue in GitHub.

The GitHub Issue MCP MCP server also includes retry handling for temporary Gemini failures and detects daily Gemini quota conditions without unnecessary retries. Model selection and retry behavior are configurable.

Limitations and notes

Duplicate scores and ranked results are candidates only. The application or AI must make the semantic duplicate decision; lexical ranking alone is not sufficient. The repository configuration is supplied through environment variables, so the material describes one configured owner and repository rather than a multi-repository selection interface.

Creating an issue is an external write operation. The documented design requires explicit human approval before the client calls the creation tool, and the Gemini agent cannot invoke that write operation autonomously.

Read the full README View source on GitHub

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Frequently Asked Questions about GitHub Issue MCP

GitHub Issue MCP is an MCP server that connects Google Gemini and the GitHub REST API for controlled issue management. Its main tools generate structured issues, find likely duplicate open issues, list issues and labels, and create approved GitHub issues. Human approval remains required before the write operation.

Install it with `npm install github-issue-mcp`, or run `npx -y github-issue-mcp` directly. The package exposes an MCP CLI that communicates over stdio, so configure your MCP-compatible client to start the command.

GitHub Issue MCP requires `GITHUB_TOKEN`, `GITHUB_OWNER`, `GITHUB_REPO`, and `GEMINI_API_KEY`. You can optionally set `GEMINI_MODEL`, `GEMINI_MAX_RETRIES`, `GEMINI_RETRY_BASE_DELAY`, and `DEBUG` to adjust Gemini behavior and debugging.

It uses `check_duplicate_issue` to retrieve open issues and rank lexical candidates, then relies on Gemini for semantic analysis. The ranked results are possible matches only, so they should not be treated as definitive duplicate decisions.

Yes. The client should display the generated issue and obtain explicit human approval before calling `create_github_issue`. The autonomous Gemini agent cannot directly access that GitHub write operation.

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