A Model Context Protocol (MCP) server that gives LLMs persistent project memory via SQLite. This eliminates the need to re-explain project context in every new conversation. The LLM queries the database and instantly knows where things stand.
- ✓Open-source license (Apache-2.0)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Documented (README)
claude mcp add mindpm -- npx -y mindpm{
"mcpServers": {
"mindpm": {
"command": "npx",
"args": ["-y", "mindpm"]
}
}
}MCP Servers overview
# mindpm
**Project memory and a control plane for AI coding agents.**
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. It also hands specced tasks to coding agents, keeps parallel agents from colliding, and only counts work as done once a human has accepted it. For agents that run unattended, an optional verifier reruns the checks itself first.
## 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, specs and acceptance criteria**, with handoff statuses, priorities and blockers
- **Decisions**: what was decided, why, and what was rejected
- **Notes and context**: architecture, bugs, ideas, tech stack, conventions
- **Sessions**: what was done and what's next, plus a brief of what changed while you were away
- **Agent attempts**: every run on a task, and what the next attempt should avoid
## Quick start
```bash
claude mcp add mindpm -e MINDPM_DB_PATH=~/.mindpm/memory.db -- npx -y mindpm
```
That's Claude Code, and `npx` fetches mindpm, so there's nothing to install first. [Claude Desktop, Cursor, VS Code, Cline and Windsurf](https://umitkavala.github.io/mindpm/setup.html#configure-your-mcp-client) use the same JSON config in a different file. Then just talk about your project. The LLM calls `start_session` to load its context, records tasks, decisions and notes as you go, and calls `end_session` to save what's next. A Kanban board runs at `http://localhost:3131`.
## How it works
```
┌──────────────┐ MCP ┌─────────┐ SQLite ┌───────────┐
│ Claude Code, │ ◄──────────► │ mindpm │ ◄────────────► │ memory.db │
│ Cursor, ... │ tools │ server │ read/write │ │
└──────────────┘ └─────────┘ └───────────┘
```
Everything stays on your machine, in one SQLite file (`~/.mindpm/memory.db` by default). mindpm can also hand specced tasks to coding agents with no conversation context: claims with leases keep parallel agents from colliding, and you accept submitted work on the board. For agents that run unattended, an optional verifier reruns the checks on each submitted commit first.
**Security:** mindpm has no user accounts and can't stop a process on your own machine. An agent with a shell can call the board's routes as you or edit the database directly. Read the [security model](https://umitkavala.github.io/mindpm/security.html) before you let agents run unattended.
## Documentation
Full documentation: **https://umitkavala.github.io/mindpm/**
- [Setup](https://umitkavala.github.io/mindpm/setup.html): every MCP client, agent instructions for any LLM, storage
- [Kanban board](https://umitkavala.github.io/mindpm/kanban-board.html): lanes, accepting work, network binding and WSL
- [Session brief](https://umitkavala.github.io/mindpm/session-brief.html): what changed while you were away
- [Agent execution](https://umitkavala.github.io/mindpm/agent-execution.html): lifecycle, specs, claims and briefs
- [Advanced: unattended agents and verification](https://umitkavala.github.io/mindpm/advanced-verification.html)
- [Security model](https://umitkavala.github.io/mindpm/security.html)
- [MCP tools](https://umitkavala.github.io/mindpm/tools.html)
- [Development](https://umitkavala.github.io/mindpm/development.html)
- [Changelog](https://github.com/umitkavala/mindpm/blob/main/CHANGELOG.md)
## License
MIT
What people ask about mindpm
What is umitkavala/mindpm?
+
umitkavala/mindpm is mcp servers for the Claude AI ecosystem. A Model Context Protocol (MCP) server that gives LLMs persistent project memory via SQLite. This eliminates the need to re-explain project context in every new conversation. The LLM queries the database and instantly knows where things stand. It has 8 GitHub stars and its last recorded update is dated 2026-10-05.
How do I install mindpm?
+
You can install mindpm by cloning the repository (https://github.com/umitkavala/mindpm) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is umitkavala/mindpm safe to use?
+
Our security agent has analyzed umitkavala/mindpm and assigned a Trust Score of 87/100 (tier: Trusted). See the full breakdown of passed checks and flags on this page.
Who maintains umitkavala/mindpm?
+
umitkavala/mindpm is maintained by umitkavala. The last recorded GitHub activity is dated 2026-10-05, with 0 open issues.
Are there alternatives to mindpm?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
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