
Mindpm
Solves the "let me remind you about my project" problem by giving LLMs a SQLite-backed memory that persists across conversations. Exposes MCP tools for managing tasks with status and priority, logging architecture decisions with reasoning, storing notes and key-value context, and tracking work sessions. Calling start_session pulls the full project state plus what you were working on last time. The LLM reads and writes directly to the database, so it picks up exactly where you left off without needing chat history. Includes a Kanban web UI served on localhost. Works across Claude Desktop, Cursor, Cline, and VS Code by pointing them all at the same database file.
- GitHub stars
- 9
- tools
- 2
- transport
- STDIO
- env vars
- 3
- last updated
- Oct 5, 2026
Tools
2 toolsPublic tool metadata for what this MCP can expose to an agent.
start_sessionThe LLM calls start_session to load its context at the beginning of a conversation.
The LLM calls start_session to load its context at the beginning of a conversation.
No parameter schema in public metadata yet.
end_sessionThe LLM calls end_session to save what's next when a session finishes.
The LLM calls end_session to save what's next when a session finishes.
No parameter schema in public metadata yet.
Sponsors
Configuration
MINDPM_DB_PATHdefault: ~/.mindpm/memory.dbPath to the SQLite database file
MINDPM_PORTdefault: 3131Port for the built-in Kanban board UI
MINDPM_HOSTdefault: 127.0.0.1Interface the Kanban UI binds to. Loopback by default; set 0.0.0.0 only to opt in (e.g. under WSL2 NAT)
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
Details
- Repository
- github.com/umitkavala/mindpm
- Category
- AI & LLM Tools
- Package
mindpm- Transport
- STDIO
- Registry
- MCP registry, active