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

| Tool | Description | |------|-------------| | create_project | Create a new project | | list_projects | List all projects | | get_project_status | Full project overview |

Tasks

| Tool | Description | |------|-------------| | create_task | Add a task | | update_task | Update status, priority, etc. | | list_tasks | List with filters | | get_task | Full task detail with sub-tasks and notes | | get_next_tasks | Smart: highest priority, unblocked |

Decisions

| Tool | Description | |------|-------------| | log_decision | Record a decision with reasoning | | list_decisions | Browse decision history |

Notes & Context

| Tool | Description | |------|-------------| | add_note | Add a note (architecture, bug, idea, etc.) | | search_notes | Full-text search | | set_context | Store key-value context | | get_context | Retrieve context |

Sessions

| Tool | Description | |------|-------------| | start_session | Get full project context + last session's next steps | | end_session | Record summary + what to do next time |

Query

| Tool | Description | |------|-------------| | query | Read-only SQL against the database | | get_project_summary | Tasks by status, blockers, recent activity | | get_blockers | All blocked tasks with what's blocking them | | search | Full-text search across everything |

How It Works

┌─────────────┐     MCP      ┌─────────┐     SQLite     ┌──────────┐
│  Claude Code │ ◄──────────► │ mindpm  │ ◄────────────► │ memory.db│
│  / Desktop   │   tools      │ server  │   read/write   │          │
└─────────────┘               └─────────┘                └──────────┘

1. You start a conversation and mention your project
2. The LLM calls start_session → gets full context
3. During the conversation, it creates tasks, logs decisions, adds notes
4. When you're done, it calls end_session → saves what's next
5. Next conversation: instant context, zero re-explanation

Storage

Default: ~/.mindpm/memory.db

Override with MINDPM_DB_PATH or PROJECT_MEMORY_DB_PATH environment variable.

Database and tables are created automatically on first run.

Development

npm install
npm run build       # Build with tsup
npm run typecheck   # Type-check without emitting
npm run dev         # Build in watch mode

License

MIT