memesh

v4.9.4

MeMesh — agentic memory for coding agents.

CodexClaude Code2 Skills1 MCP serverstdio

By PCIRCLE AILicense: MIT15 GitHub starsUpdated last week

Directory evidence

Runtimes: Codex and Claude Code
Parsed components: 3 skill or MCP entries
Source updated: Sep 10, 2026
Manifest status: Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install memesh for Codex and Claude Code

Installs for the current user

codex plugin marketplace add IchenDEV/agent-plugin-mkt
codex plugin marketplace upgrade agent-plugin-marketplace
codex plugin add memesh@agent-plugin-marketplace

Paste and run these commands in a terminal with Codex. They add and refresh the PluginsMP catalog, then install this plugin.

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually

$ git clone https://github.com/PCIRCLE-AI/memesh

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The repository root is the plugin root.

Plugin files

memesh/

├── .codex-plugin/plugin.json
├── .claude-plugin/plugin.json
├── skills/memesh/SKILL.md
├── skills/memesh-review/SKILL.md
└── .mcp.json

Included Skills2

memeshskills/memesh/SKILL.md

Use MeMesh to remember, recall, and manage AI knowledge across sessions, and to exchange task-focused messages with local agents. Triggers when the user asks to remember something, recall past decisions, forget outdated info, learn from mistakes, analyze work patterns, contact another agent, or handle a memesh_message or legacy memesh_message_available notification. Also triggers when the user asks "what do you remember", "where did we leave off", or wants to catch up on a project; when a session starts and project context is needed; and proactively when you make important decisions, fix bugs, learn lessons worth preserving, or owe another agent a requested result or disposition.

memesh-reviewskills/memesh-review/SKILL.md

Review and optimize the MeMesh memory database. Analyzes health score, finds stale or noisy memories, shows work patterns, and suggests human-reviewed cleanup actions. Use when asked to "review memories", "check memory health", "clean up knowledge", or "what's in my memory".

MCP servers1

memeshstdio

command: node
args: ./dist/mcp/server.js
cwd: .

Plugin manifests2

.codex-plugin/plugin.json

{
  "name": "memesh",
  "description": "MeMesh — agentic memory for coding agents.",
  "version": "4.9.4",
  "mcpServers": "./.codex-plugin/mcp.json"
}

.claude-plugin/plugin.json

{
  "name": "memesh",
  "description": "MeMesh — agentic memory for coding agents. Captured from the agent's real work via hooks, recalled when it acts. One SQLite file, zero cloud required.",
  "author": {
    "name": "PCIRCLE AI"
  },
  "version": "4.9.4",
  "mcpServers": "./.claude-plugin/mcp.json",
  "homepage": "https://github.com/PCIRCLE-AI/memesh",
  "repository": "https://github.com/PCIRCLE-AI/memesh",
  "license": "MIT",
  "keywords": [
    "claude-code",
    "mcp",
    "knowledge-graph",
    "agentic-memory",
    "agent-memory",
    "ai-memory"
  ]
}