Power your agent
पब्लिशर की अपनी कमांड। PlugMCP एंडपॉइंट नहीं।
Host a copy with our keys and logs.
uvx cp-memory-mcp==1.8.1Claude Code में लोकल कमांड के लिए इंस्टॉल लिंक नहीं है। नीचे दी गई कमांड कॉपी करें और टर्मिनल में चलाएँ।
claude mcp add io.github.cjhuochai-cp-memory -- uvx cp-memory-mcp==1.8.1टर्मिनल में चलाएँ।
{ "mcpServers": { "io.github.cjhuochai-cp-memory": { "command": "uvx", "args": [ "cp-memory-mcp==1.8.1" ] } }}claude_desktop_config.json
रिमोट URL या आपकी मशीन पर कमांड? दोनों इंस्टॉल में क्या अंतर है
PlugMCP पर चलाएँ
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
लॉन्चपब्लिशर से
For reproducible package, protocol and recall checks, see verification evidence and limits.
~/.cp-memory/memory.db by default.Local-first, governable long-term memory for AI coding agents
With Python 3.10+ and uv installed, any stdio MCP client can start CP Memory with:
uvx cp-memory-mcp
The public package passed a clean-cache MCP handshake with all 40 tools and a write/search/correct flow. See MCP client setup for Codex, Claude Code, Cursor, VS Code, and Gemini CLI examples.
For the enhanced Codex integration with lifecycle Hooks and Skills, install the plugin:
codex plugin marketplace add CJhuochai/cp-memory
codex plugin add cp-memory@cp-memory
Restart Codex after installation and approve the lifecycle Hooks if prompted.
CP Memory is a local-first memory plugin for Codex. It stores facts, preferences, ongoing work, episodes, decisions, and conversation checkpoints in a local SQLite database, then restores relevant context through MCP tools and lifecycle hooks.
The goal is not to remember as much as possible. The goal is memory that remains trustworthy after long-term use: explainable, reviewable, correctable, and governable.
repo:, project:, and workspace: scopes.
You tell Codex:
Remember this: releases for this project must start on a branch, run tests, and merge through a PR.
In a later session, you ask:
What are the release rules for this plugin?
CP Memory restores the relevant memory from the local primary store first, and Codex follows that rule. If the memory is wrong, you can mark it wrong, mark it stale, or write a corrected version.
See more anonymized examples in docs/examples.md.
For a GIF, short video, or launch post, use the sanitized 30-second demo script.
For any stdio MCP client, use the verified public package:
uvx cp-memory-mcp
Client-specific commands and JSON files are in docs/mcp-clients.md.
For Windows, the recommended path is GitHub Marketplace installation:
codex plugin marketplace add CJhuochai/cp-memory
codex plugin add cp-memory@cp-memory
Restart Codex after installation. If Codex asks you to trust hooks, approve the CP Memory lifecycle hooks in the hooks view.
For macOS/Linux, use the source installer. It creates a private Python runtime for the plugin and installs the MCP dependency:
git clone https://github.com/CJhuochai/cp-memory.git
cd cp-memory
sh ./install.sh
Restart Codex when it finishes. Do not treat GitHub Marketplace installation on macOS/Linux as an equivalently verified path: Marketplace does not run install.sh, so it does not create that private runtime.
Manual smoke testing of real Codex desktop Hook injection on macOS/Linux is still pending access to physical devices. This release is accepted through three-platform CI; the boundary does not affect the installer and MCP-startup checks already covered, but it is not a substitute for full desktop manual acceptance.
memory.db, logs, private summaries, or environment files.If you have seen other memory projects, start with docs/comparison.md. CP Memory's main difference is Codex lifecycle integration plus memory governance, not just storage and search.
See docs/roadmap.md for future directions. The roadmap prioritizes local-first behavior, explainability, correctability, and privacy safety.
See CHANGELOG.md for version history.
Windows users normally do not need to run install.ps1. It is mainly for local development, refreshing the personal marketplace cache, and migrating old global hook wiring from earlier versions.
For local macOS/Linux development, run:
sh ./install.sh
sh ./scripts/test-install.sh
Python 3 with python3 on PATH is required. The installer creates a private virtual environment in the plugin directory and installs runtime dependencies; this is the currently verified installation path for macOS/Linux.
Run the test suite:
python -m unittest discover -s tests -p test_cp_memory.py
Validate the installer in an isolated temporary profile without touching your real Codex configuration:
powershell -ExecutionPolicy Bypass -File .\scripts\test-install.ps1
MIT
Local-first, governable long-term memory for AI coding agents
{ "mcpServers": { "io.github.cjhuochai-cp-memory": { "command": "uvx", "args": [ "cp-memory-mcp==1.8.1" ] } }}टूल
अभी टूल सूची नहीं है। रिमोट सर्वर को पहले हेल्थ चेक के बाद सूची मिलती है।
FAQ
इस पेज पर Cursor, Claude Desktop, Claude Code या VS Code के लिए stdio कॉन्फ़िग कॉपी करें। यह पब्लिशर का इंस्टॉल इस्तेमाल करता है, PlugMCP प्रॉक्सी नहीं।
इस रिकॉर्ड में कोई ज़रूरी एनवायरनमेंट वेरिएबल दर्ज नहीं है।
CP Memory stdio पर लोकल चलता है।
पिछली जाँच 2026-11-08 को हुई। Local-first, governable long-term memory for AI coding agents