mindpm

Persistent project memory for LLMs. Never re-explain your project again.

mindpm is an MCP (Model Context Protocol) server that gives LLMs a SQLite-backed brain for your projects. It tracks tasks, decisions, architecture notes, and session context — so every new conversation picks up exactly where you left off.

The Problem

Every new LLM chat starts from zero:

• "Let me remind you about my project..."
• "Last time we decided to use Redis for..."
• "Where did we leave off?"

The Solution

mindpm persists your project state in a local SQLite database. The LLM reads and writes to it via MCP tools. No chat history needed. No memory features needed.

You: "What should I work on next?"
LLM: [queries mindpm] "Last session you finished the auth refactor.
      You have 3 high-priority tasks: rate limiting, API docs, and
      the webhook retry bug. Rate limiting is unblocked — start there."

What It Tracks

• Tasks — status, priority, blockers, sub-tasks
• Decisions — what was decided, why, what alternatives were rejected
• Notes — architecture, bugs, ideas, research
• Context — key-value pairs (tech stack, conventions, config)
• Sessions — what was done, what's next

Kanban Board

mindpm includes a built-in Kanban UI. When the MCP server starts, it serves a web interface at http://localhost:3131.

Every start_session call returns a direct link to your project's board:

Kanban board: http://localhost:3131?project=<project-id>

The port is configurable via the MINDPM_PORT environment variable.

Setup

Install

npm install -g mindpm

Or run from source:

git clone https://github.com/umitkavala/mindpm.git
cd mindpm
npm install
npm run build

Configure your MCP client

All clients use the same JSON format — just different config file locations. They all share the same ~/.mindpm/memory.db, so you can switch tools mid-project without losing context.

Claude Code — ~/.claude/claude_desktop_config.json

{
  "mcpServers": {
    "mindpm": {
      "command": "mindpm",
      "env": {
        "MINDPM_DB_PATH": "~/.mindpm/memory.db",
        "MINDPM_PORT": "3131"
      }
    }
  }
}

Or use the one-liner:

claude mcp add mindpm -e MINDPM_DB_PATH=~/.mindpm/memory.db -- npx -y mindpm

Cursor — .cursor/mcp.json in your project root (or ~/.cursor/mcp.json globally)

{
  "mcpServers": {
    "mindpm": {
      "command": "npx",
      "args": ["-y", "mindpm"],
      "env": {
        "MINDPM_DB_PATH": "~/.mindpm/memory.db"
      }
    }
  }
}

VS Code + Copilot — .vscode/mcp.json in your project root

{
  "servers": {
    "mindpm": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "mindpm"],
      "env": {
        "MINDPM_DB_PATH": "~/.mindpm/memory.db"
      }
    }
  }
}

Cline — Add via VS Code settings → Cline → MCP Servers, or edit cline_mcp_settings.json:

{
  "mcpServers": {
    "mindpm": {
      "command": "npx",
      "args": ["-y", "mindpm"],
      "env": {
        "MINDPM_DB_PATH": "~/.mindpm/memory.db"
      }
    }
  }
}

Windsurf — Settings → Cascade → MCP, using the same JSON structure as Cline above.

Using mindpm with any LLM

On first run, mindpm writes ~/.mindpm/AGENT.md — a ready-to-paste system prompt that tells your LLM how to use mindpm proactively. Paste its contents into your client's custom instructions or system prompt box.

You can also call the get_agent_instructions tool at any time to retrieve the instructions.

Start Using

That's it. The LLM now has access to mindpm tools. Just start talking about your projects.

MCP Tools

Projects

Tasks

... View full README on GitHub