
Mindpm
io.github.umitkavalaPublished by GitHub account umitkavalav3.2.0Updated Oct 24, 2026
Project memory and a control plane for AI coding agents.
Overview
Local MCP server that gives AI coding agents a SQLite-backed project memory for tasks, decisions, notes and sessions, plus a Kanban board.
- What you can do
- Record and query tasks, specs, acceptance criteria, priorities and blockers
- Capture decisions with rationale and rejected options, plus notes on architecture, bugs and conventions
- Start and end sessions so a new conversation resumes with what was done and what is next
- Hand specced tasks to coding agents with claims and leases, and log each agent attempt
- Accept submitted work on a built-in Kanban board, with an optional verifier rerunning checks
- When to use it
- Useful when you work on a project across many separate AI chat sessions and want the assistant to pick up context without re-explaining it, or when several coding agents work on the same task list and need coordination.
- Requirements
- Runs locally over stdio, typically via npx with no prior install. Needs a SQLite database file, set with MINDPM_DB_PATH (defaults to a file under the user's home directory). Optional MINDPM_HOST and MINDPM_PORT configure the built-in Kanban board, served on localhost port 3131 by default. Desktop MCP clients only.
Installation
In SourceWeft
- Open Mindpm in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
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.
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
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.
How it works
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.
Documentation
Full documentation: https://umitkavala.github.io/mindpm/
- Setup: every MCP client, agent instructions for any LLM, storage
- Kanban board: lanes, accepting work, network binding and WSL
- Session brief: what changed while you were away
- Agent execution: lifecycle, specs, claims and briefs
- Advanced: unattended agents and verification
- Security model
- MCP tools
- Development
- Changelog
License
MIT
Source: README.md at commit 4c194fd
Tools
0Version history
3- v3.2.0LatestOct 5, 2026
- v3.1.1Oct 5, 2026
- v1.2.41Sep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts