What is Cunzhi?
Cunzhi is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to 告别ai提前终止烦恼，助力ai更加持久
告别AI提前终止烦恼，助力AI更加持久
This server falls under the Knowledge & Memory category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- 告别AI提前终止烦恼，助力AI更加持久
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx cunzhiConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Cunzhi
Cunzhi (寸止) is a Rust-based MCP server that solves the frustrating problem of AI assistants terminating conversations prematurely before a task is fully resolved. When the AI would normally end the dialogue, Cunzhi intercepts that action and presents configurable continuation options, keeping the session alive until the problem is truly solved. It also includes a memory management system that stores project-specific development standards and preferences, and a semantic code search tool so the AI can navigate large codebases more effectively. Developers working on complex, multi-step tasks use Cunzhi to maintain continuity in agentic workflows without manually re-prompting the AI to continue.
Prerequisites
- macOS or Linux operating system (Homebrew available on macOS for easy install)
- The cunzhi and dengYiXia executables on your system PATH if installing manually from the releases page
- An MCP client such as Claude Desktop, Cursor, or Windsurf that supports stdio MCP servers
Install via Homebrew (macOS)
The easiest installation method on macOS is through the official Homebrew tap, which installs both the cunzhi MCP server and the dengYiXia settings utility.
brew tap imhuso/cunzhi && brew install cunzhiInstall manually from releases (Linux / Windows)
Download the cunzhi and dengYiXia binaries from the GitHub releases page for your platform. Move both executables to a directory on your PATH such as /usr/local/bin.
# After downloading the release archive:
chmod +x cunzhi dengYiXia
sudo mv cunzhi dengYiXia /usr/local/bin/Add Cunzhi to your MCP client configuration
Register the cunzhi server in your MCP client's configuration file. No environment variables are required for basic operation.
Open the settings interface to configure continuation options
Run the dengYiXia settings utility to configure which continuation prompts Cunzhi presents when the AI tries to end the conversation. You can set project-specific memory here as well.
dengYiXiaTest the interception behavior
Give your AI assistant a complex, multi-step task. When the AI would normally wrap up and stop, Cunzhi will intercept and display your configured continuation options, allowing you to choose how to proceed without re-establishing context.
Cunzhi Examples
Client configuration
Claude Desktop configuration for Cunzhi. The server requires no environment variables for basic use.
{
"mcpServers": {
"cunzhi": {
"command": "cunzhi"
}
}
}Prompts to try
Example prompts that demonstrate Cunzhi's value in keeping long agentic sessions alive.
- "Refactor all the API handlers in this repository to use the new error handling pattern. Don't stop until every file is updated."
- "Review this entire codebase for security issues and fix each one you find."
- "Search the codebase for all usages of the deprecated fetch() wrapper and migrate them to the new httpClient module."
- "Keep working on this feature until all tests pass — do not end the session."
- "What development standards have you remembered for this project?"Troubleshooting Cunzhi
cunzhi: command not found after Homebrew install
Run 'brew link cunzhi' to ensure the binary is symlinked into your PATH. Also run 'echo $PATH' to confirm /usr/local/bin or /opt/homebrew/bin is included, then restart your terminal.
The AI still terminates sessions even with Cunzhi running
Confirm the MCP server appears in your client's active server list and that there are no connection errors in the client logs. Also open dengYiXia settings to verify that continuation prompts are configured — an empty prompt list means no interception will occur.
dengYiXia settings GUI does not open
Make sure both cunzhi and dengYiXia binaries are on your PATH and are executable. On macOS, if Gatekeeper blocks the binary, run 'xattr -d com.apple.quarantine $(which dengYiXia)' to remove the quarantine attribute.
Frequently Asked Questions about Cunzhi
What is Cunzhi?
Cunzhi is a Model Context Protocol (MCP) server that 告别ai提前终止烦恼，助力ai更加持久 It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Cunzhi?
Follow the installation instructions on the Cunzhi GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Cunzhi?
Cunzhi works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Cunzhi free to use?
Yes, Cunzhi is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
Cunzhi Alternatives — Similar Knowledge & Memory Servers
Looking for alternatives to Cunzhi? Here are other popular knowledge & memory servers you can use with Claude, Cursor, and VS Code.
MemPalace
★ 52.6kA local AI memory system that stores all conversations verbatim and organizes them into navigable structures. It provides 19 MCP tools for AI assistants to search and retrieve past decisions, debugging sessions, and architecture debates automatically
Kratos
★ 25.7k🏛️ Memory System for AI Coding Tools - Never explain your codebase again. MCP server with perfect project isolation, 95.8% context accuracy, and the Four Pillars Framework.
Context Mode
★ 15.4kAn MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programm
Memu
★ 13.7kMemory for 24/7 proactive agents like OpenClaw.
MemOS
★ 9.3kMemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, u
Everos
★ 5.4kBuild, evaluate, and integrate long-term memory for self-evolving agents.
Browse More Knowledge & Memory MCP Servers
Explore all knowledge & memory servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up Cunzhi in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use Cunzhi?
Browse our complete directory of 33,000+ MCP servers, read setup guides for your editor, and start building with the Model Context Protocol.