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.
Backlog MCP Server
@MCP-Mirror
Basic information
About Backlog MCP Server
Mirror of
Backlog MCP Server config
Add this server to your MCP-compatible client using the configuration below.
{
"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"
}
}
}
}Backlog MCP Server tools
Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
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
Frequently asked questions
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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