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Give AI persistent project memory to resume tasks and context seamlessly.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mindpm" yet — see the docs or source repo.
Read the project's persistent memory and summarize recent tasks, key decisions, notes, and sessions. Then tell me what to do next.
A summary of the current project state and recommended next actions.
List the tasks in the current Kanban board, group them by status, and highlight the highest-priority items.
A task list grouped by status, with the most urgent items highlighted.
Generate a brief from the latest session record and git activity, summarizing what was completed, what remains, and the relevant context.
A session brief that helps with handoff or continuing the work.
Developers or product managers can use it to preserve tasks, decisions, and context across multiple days and sessions. This helps an AI quickly understand the current state and continue the work.
Teams can continuously record key decisions, notes, and session information while working on requirements, implementation, or troubleshooting. This makes it easier to trace rationale and background later.
When work is handed off between team members or AI sessions, session briefs and git activity help explain recent progress quickly. The next person can continue without reconstructing everything from scratch.
It is an MCP server that provides persistent project memory with SQLite. It tracks tasks, decisions, notes, sessions, and context, and includes a Kanban board and session briefs.
It allows an LLM to restore project state from stored memory and resume tasks using session briefs and git activity. It is useful for collaboration that requires long-term context.
The provided information only states that it uses SQLite and does not include installation steps or other prerequisites. See the source repository for details.
An MCP server for persistent memory, knowledge bases, and project summaries.
Give AI coding assistants persistent memory and full-text knowledge retrieval.
Give LLMs persistent, searchable access to project knowledge and session context.
Store project rules, context, and decisions for reuse across MCP clients.
Give local AI coding assistants persistent memory and semantic code search.
Give AI assistants persistent project memory that can be queried and taught.