Backlog Manager MCP Server

Backlog Manager is an MCP (Machine-Consumable Programming) server for issue and task management with a file-based approach. It provides tools for AI

Local serverstdioPython

What is the Backlog Manager MCP MCP server?

Backlog manager mcp mcp server connects Backlog Manager MCP to AI assistants that speak the Model Context Protocol. Backlog Manager is an MCP (Machine-Consumable Programming) server for issue and task management with a file-based approach. It provides tools for AI agents and other clients to create issues, add tasks to them, and track task status. Issues represent high-level feature requests or bugs, while tasks.

What Backlog Manager MCP does

Backlog Manager is an MCP (Machine-Consumable Programming) server for issue and task management with a file-based approach. It provides tools for AI agents and other clients to create issues, add tasks to them, and track task status. Issues represent high-level feature requests or bugs, while tasks represent specific work items needed to resolve the issue.

Key capabilities

  • Issue Management — Create, list, select, and track issues with descriptions
  • Task Tracking — Add tasks to issues with titles, descriptions, and status tracking
  • Status Workflow — Track task progress through New, InWork, and Done states
  • File-Based Storage — Portable JSON storage format for easy backup and version control
  • Flexible Transport — Support for both SSE (HTTP) and stdio communication
  • Docker Support — Run in containers for easy deployment and isolation

Installing the backlog manager mcp mcp server

The server is distributed via a container image as backlog/manager, so most clients can run it without a manual build step. Add it to your MCP client's configuration and restart the client to pick it up — the copy-paste configs for Claude Desktop, Claude Code and Cursor are on this page.

Configuration

The server reads 2 environment variables: TRANSPORT, TASKS_FILE. Keep credentials in your client's env block or a secrets manager rather than committing them.

Requirements

  • Python: 3.12 or higher - Package Manager: uv (recommended) or pip - Docker: (Optional) For containerized deployment - MCP Client: Claude Code, Windsurf, or any other MCP-compatible client

Where it fits

Productivity servers pay off through capture: the tasks and notes that never get filed are the ones where opening the app is more friction than the thought is worth. Backlog Manager MCP sits in that group. Worth comparing against the other productivity servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.

Practical notes

  • This server runs locally, so it operates with whatever access your machine and its credentials already have. Scope that deliberately rather than by default.
  • Maintained by danielscholl, written in Python.
  • MCP clients ask for confirmation before each tool call by default. Keep that on while you learn what the backlog manager mcp mcp server actually does with your data.
  • Every entry in this directory is reviewed by hand before it goes live, and details are checked against the project's own documentation.

How to install the Backlog Manager MCP MCP server

{
  "mcpServers": {
    "backlog-manager": {
      "transport": "sse",
      "url": "http://localhost:8050/sse"
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Python: 3.12 or higher - Package Manager: uv (recommended) or pip - Docker: (Optional) For containerized deployment - MCP Client: Claude Code, Windsurf, or any other MCP-compatible client
VariableDescriptionRequired
TRANSPORTConfiguration value read at startup.Optional
TASKS_FILEConfiguration value read at startup.Optional

Frequently asked questions

It connects Backlog Manager MCP to MCP-compatible AI assistants such as Claude and Cursor. Instead of copying data back and forth by hand, the assistant works with Backlog Manager MCP directly.