jhawkins11/task-manager-mcp

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Node.js MCP server using LLMs (Gemini/OpenRouter) for AI-assisted task planning, breakdown, and code review. Designed for Cursor integration.

概要

This is an MCP server built to integrate with AI code editors like Cursor. The main goal here is to maximize Cursor's agentic capabilities and Gemini 2.5's excellent architecting capabilities while working around Cursor's extremely limited context window. This was inspired largely by Roo Code's Boomerang mode, but I found it extremely expensive as the only model that works with it's apply bot is Claude 3.7 Sonnet. With this server, you get the best of both worlds: unlimited context window and unlimited usage for the price of Cursor's $20/month subscription. In addition, it includes a Svelte UI that allows you to view the task list and progress, manually adjust the plan, and review the changes. - Give it a feature description, and it uses an LLM with project context via repomix to generate a step-by-step coding plan for the AI agent to follow with recursive task breakdown for high-effort tasks.

README

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Task Manager MCP Server

This is an MCP server built to integrate with AI code editors like Cursor. The main goal here is to maximize Cursor’s agentic capabilities and Gemini 2.5’s excellent architecting capabilities while working around Cursor’s extremely limited context window. This was inspired largely by Roo Code’s Boomerang mode, but I found it extremely expensive as the only model that works with it’s apply bot is Claude 3.7 Sonnet. With this server, you get the best of both worlds: unlimited context window and unlimited usage for the price of Cursor’s $20/month subscription.

In addition, it includes a Svelte UI that allows you to view the task list and progress, manually adjust the plan, and review the changes.

Svelte UI

Core Features

Complex Feature Planning: Give it a feature description, and it uses an LLM with project context via repomix to generate a step-by-step coding plan for the AI agent to follow with recursive task breakdown for high-effort tasks.
Integrated UI Server: Runs an Express server to serve static frontend files and provides basic API endpoints for the UI. Opens the UI in the default browser after planning is complete or when clarification is needed and displays the task list and progress.
Unlimited Context Window: Uses Gemini 2.5’s 1 million token context window with repomix’s truncation when needed.
Conversation History: Keeps track of the conversation history for each feature in a separate JSON file within .mcp/features/ for each feature, allowing Gemini 2.5 to have context when the user asks for adjustments to the plan.
Clarification Workflow: Handles cases where the LLM needs more info, pausing planning and interacting with a connected UI via WebSockets.
Task CRUD: Allows for creating, reading, updating, and deleting tasks via the UI.
Code Review: Analyzes git diff HEAD output using an LLM and creates new tasks if needed.
Automatic Review (Optional): If configured (AUTO_REVIEW_ON_COMPLETION=true), automatically runs the code review process after the last original task for a feature is completed.
Plan Adjustment: Allows for adjusting the plan after it’s created via the adjust_plan tool.

Setup

Prerequisites:

Node.js
npm
Git

Installation & Build:

Clone:

git clone https://github.com/jhawkins11/task-manager-mcp.git
cd task-manager-mcp

Install Backend Deps:
```
npm install
```
Configure: You’ll configure API keys later directly in Cursor’s MCP settings (see Usage section), but you might still want a local .env file for manual testing (see Configuration section).
Build: This command builds the backend and frontend servers and copies the Svelte UI to the dist/frontend-ui/ directory.
```
npm run build
```

Running the Server (Manually):

GitHub で README 全文を見る

インストール

This server does not publish a one-line install command.

Open the repository installation guide MCP 初心者？mcpskill.org のガイドから始めましょう →

設定

{
  "mcpServers": {
    "task-manager-mcp": {
      "command": "node",
      "args": ["/full/path/to/your/task-manager-mcp/dist/server.js"],
      "env": {
        "OPENROUTER_API_KEY": "sk-or-v1-xxxxxxxxxxxxxxxxxxxx"
        //   optional: my recommended model for MCP is Gemini 2.5 Pro Free which is already set by default
        //   "OPENROUTER_MODEL": "google/gemini-2.5-flash-preview:thinking",
        //   also optional
        //   "FALLBACK_OPENROUTER_MODEL": "google/gemini-2.5-flash-preview:thinking",
        //   optional: the default port for the UI is 4999 if not set
        //   "UI_PORT": "4999",
        //   optional: the default port for the WebSocket server is 4999 if not set
        //   "WS_PORT": "4999"
        // Add GEMINI_API_KEY here instead if using Google directly
        // Add any other necessary env vars here
      }
    }
    // Add other MCP servers here if you have them
  }
}