Mindpm

io.github.umitkavalaPublished by GitHub account umitkavalav3.2.0Updated Oct 24, 2026

Project memory and a control plane for AI coding agents.

Overview

AI-generated 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.
Before you install
No user accounts or authentication: any process on the machine, including an agent with a shell, can call the board's routes or edit the database directly. Binding the board to 0.0.0.0 via MINDPM_HOST exposes it beyond loopback. Agents can write, claim and submit tasks, and unattended runs are only gated by an optional verifier.

Installation

In SourceWeft

  1. Open Mindpm in the dashboard and add it to a workspace.
  2. 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.

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 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 before you let agents run unattended.

Documentation

Full documentation: https://umitkavala.github.io/mindpm/

License

MIT

Source: README.md at commit 4c194fd

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

3
  1. v3.2.0LatestOct 5, 2026
  2. v3.1.1Oct 5, 2026
  3. 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