io.github.umitkavala/mindpm

编码与调试

by umitkavala

通过 SQLite 为 LLMs 提供持久化项目记忆,避免反复重新解释项目背景与上下文。

什么是 io.github.umitkavala/mindpm

通过 SQLite 为 LLMs 提供持久化项目记忆,避免反复重新解释项目背景与上下文。

README

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.

code
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:

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

The port is configurable via the MINDPM_PORT environment variable.

Setup

Install

bash
npm install -g mindpm

Or run from source:

bash
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

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

Or use the one-liner:

bash
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)

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

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

json
{
  "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:

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

ToolDescription
create_projectCreate a new project
list_projectsList all projects
get_project_statusFull project overview

Tasks

ToolDescription
create_taskAdd a task
update_taskUpdate status, priority, etc.
list_tasksList with filters
get_taskFull task detail with sub-tasks and notes
get_next_tasksSmart: highest priority, unblocked

Decisions

ToolDescription
log_decisionRecord a decision with reasoning
list_decisionsBrowse decision history

Notes & Context

ToolDescription
add_noteAdd a note (architecture, bug, idea, etc.)
search_notesFull-text search
set_contextStore key-value context
get_contextRetrieve context

Sessions

ToolDescription
start_sessionGet full project context + last session's next steps
end_sessionRecord summary + what to do next time

Query

ToolDescription
queryRead-only SQL against the database
get_project_summaryTasks by status, blockers, recent activity
get_blockersAll blocked tasks with what's blocking them
searchFull-text search across everything

How It Works

code
┌─────────────┐     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

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

License

MIT

常见问题

io.github.umitkavala/mindpm 是什么?

通过 SQLite 为 LLMs 提供持久化项目记忆,避免反复重新解释项目背景与上下文。

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