Enterprise DNA
M MCP Servers Developer low

riponcm/projectmem

by Various

Local-first memory layer for AI coding agents. Captures issues, attempts, decisions, and cross-project library gotchas — your AI starts experienced, not amnesiac. Native MCP server

R

MCP

riponcm/projectmem

Added 19 June 2026

#ai-agents #ai-memory #ai-memory-layer #ai-tools #antigravity #claude-code #codex #coding-assistant

Overview

A local-first memory layer for AI coding agents that captures issues, attempts, decisions, and cross-project library gotchas. It runs as a native MCP server verified across Claude Desktop, Cursor, Antigravity, and Codex, keeping all data 100% local with no cloud or telemetry.

Best for

Best for
Developers who want persistent, private memory for AI coding agents across sessions.

Use cases

  • Persisting AI agent context across coding sessions to avoid repeating past discoveries
  • Recording cross-project library pitfalls so agents learn from related work
  • Storing decision logs for complex debugging or refactoring tasks

How to use

Install

pip install projectmem\ncd your-project\npjm init

Tools exposed

  • pip
  • git

Notes

A local-first memory layer for AI coding agents that captures issues, attempts, decisions, and cross-project library gotchas. It runs as a native MCP server verified across Claude Desktop, Cursor, Antigravity, and Codex, keeping all data 100% local with no cloud or telemetry.

19 stars on GitHub. Last updated 2026-06-18. Licensed MIT.

Use cases

  • Persisting AI agent context across coding sessions to avoid repeating past discoveries
  • Recording cross-project library pitfalls so agents learn from related work
  • Storing decision logs for complex debugging or refactoring tasks

Pros

  • No cloud dependency or telemetry — fully offline and private
  • Works with multiple agent frontends via standard MCP protocol
  • Low overhead: Python-based and easy to integrate into existing workflows

Cons

  • Small community (19 stars) — limited long-term support or roadmap
  • Requires manual setup and configuration of the MCP server
  • No built-in sharing or syncing between multiple machines

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • No cloud dependency or telemetry — fully offline and private
  • Works with multiple agent frontends via standard MCP protocol
  • Low overhead: Python-based and easy to integrate into existing workflows

Cons

  • Small community (19 stars) — limited long-term support or roadmap
  • Requires manual setup and configuration of the MCP server
  • No built-in sharing or syncing between multiple machines

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

Free 27-page guide

Get the free Developer’s Field Guide

A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.

Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.

No spam. Unsubscribe any time.

Running a business, not writing the code? See the MCP servers picked for operators, and get your first one wired up with us.

Operator picks