Project memory and a control plane for AI coding agents.
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io.github.umitkavala/mindpm is an MCP server that project memory and a control plane for AI coding agents. Its tool list has not been published yet over stdio and http, requires no API key, and scores 80/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"mindpm": {
"env": {
"MINDPM_PORT": "3131",
"MINDPM_DB_PATH": "~/.mindpm/memory.db"
},
"command": "mindpm"
}
}
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Project memory and a control plane for AI coding agents.
Run this in your terminal to verify the server starts. Then let us know if it worked - your result helps other developers.
npx -y 'mindpm' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
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No known CVEs.
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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.
Every new LLM chat starts from zero:
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."
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 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.
┌──────────────┐ 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 before you let agents run unattended.
Full documentation: https://umitkavala.github.io/mindpm/