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Backlog MCP Server

@MCP-Mirror

Backlog MCP Server について

Mirror of

基本情報

カテゴリ

その他

ライセンス

MIT license

ランタイム

node

トランスポート

stdio

公開者

MCP-Mirror

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "backlog": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "BACKLOG_DOMAIN",
        "-e",
        "BACKLOG_API_KEY",
        "ghcr.io/nulab/backlog-mcp-server"
      ],
      "env": {
        "BACKLOG_DOMAIN": "your-domain.backlog.com",
        "BACKLOG_API_KEY": "your-api-key"
      }
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Backlog MCP Server?

A Model Context Protocol (MCP) server that enables AI agents like Claude Desktop, Cline, and Cursor to interact with the Backlog API. It provides tools for managing projects, issues, wiki pages, Git repositories, pull requests, notifications, and watching items.

How to use Backlog MCP Server?

Configure the server in your MCP‑compatible client using Docker (recommended) or a manual Node.js installation. Set environment variables BACKLOG_DOMAIN (your Backlog domain) and BACKLOG_API_KEY (your API key). Optional variables MAX_TOKENS and OPTIMIZE_RESPONSE control response size and field selection.

Key features of Backlog MCP Server

  • Project management (CRUD operations)
  • Issue tracking with comments
  • Wiki page management
  • Git repository management
  • Pull request management with comments
  • Notification and watching list management
  • GraphQL‑style field selection for optimized responses
  • Configurable token limiting for large responses

Use cases of Backlog MCP Server

  • List all projects and their details through natural language
  • Create, update, or delete issues with priority and type
  • Retrieve and filter issues by project or status
  • Manage pull requests, including creating and commenting
  • Fetch watching items and notification counts

FAQ from Backlog MCP Server

What are the dependencies and runtime requirements?

The server runs via Docker or Node.js (after building from source). You need a Backlog account with API access and a valid API key. Docker is the simplest deployment method.

Where does my data live?

All data remains in your Backlog space. The server is stateless; it only makes API calls to Backlog and does not store any data locally.

How can I limit response size or select only specific fields?

Set MAX_TOKENS (default 50 000) to cap token usage, and set OPTIMIZE_RESPONSE=true to enable GraphQL‑style field selection in your queries.

Can I customize tool descriptions or use a different language?

Yes. Create a .backlog-mcp-serverrc.json file in your home directory, or set environment variables (e.g., BACKLOG_MCP_TOOL_ADD_ISSUE_COMMENT_DESCRIPTION). A Japanese translation template is provided.

How do I keep the Docker image up‑to‑date?

Add --pull always to the Docker run arguments, or manually run docker pull ghcr.io/nulab/backlog-mcp-server:latest.

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