What authentication is required?
A GitHub personal access token must be provided via the `GITHUB_PERSONAL_ACCESS_TOKEN` environment variable.
@wjessup
基本信息
Extended GitHub MCP Server with additional tools for pull request review comment functionality
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"github-mcp-server-review-tools": {
"command": "docker",
"args": [
"build",
"-t",
"mcp/github",
"-f",
"src/github/Dockerfile",
"."
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Github Mcp Server Review Tools is an MCP server that provides tools for interacting with GitHub pull request reviews, comments, and threads. It enables developers to fetch, reply, resolve, and check review threads via a Model Context Protocol–compatible client such as Cursor.
Install the project with yarn && yarn start. Configure the server in your MCP client (e.g., Cursor) by setting the command to node with the path to the compiled dist/index.js and providing a GITHUB_PERSONAL_ACCESS_TOKEN environment variable. Use the tools listed in the README to perform review operations.
A GitHub personal access token must be provided via the `GITHUB_PERSONAL_ACCESS_TOKEN` environment variable.
Node.js and Yarn are required to build and run the server from source.
A Dockerfile is included (`src/github/Dockerfile`) but has not been tested by the author.
All data is accessed via the GitHub API using the provided personal access token. No local storage is mentioned.
The server follows the Model Context Protocol, which typically uses stdio transport; the README does not specify alternative transports.
Node.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.
Yuque mcp server
a private MCP server for accessing Linear
Join.cloud lets AI agents work together in real-time rooms. Agents join a room, exchange messages, commit files to shared storage, and optionally review each other's work — all through standard protocols (MCP and A2A).
MCP server connecting AI assistants with Jira & Confluence for smart project management.
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