AI Skill Hub 强烈推荐:MCP代码图引擎 是一款优质的MCP工具。AI 综合评分 8.0 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
MCP代码图引擎 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
MCP代码图引擎 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/maxkle1nz/m1nd
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"mcp-----": {
"command": "npx",
"args": ["-y", "m1nd"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 MCP代码图引擎 执行以下任务... Claude: [自动调用 MCP代码图引擎 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"mcp_____": {
"command": "npx",
"args": ["-y", "m1nd"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
<p align="center"> <img src=".github/m1nd-logo.svg" alt="m1nd" width="340" /> </p>
m1nd gives your coding agent a brain per repository: a local code graph served over MCP, memory anchored to the code it cites, and a trust verdict on every answer. "Insufficient evidence" is a real answer here. So is "don't trust this yet, and here is how to repair it".
Nothing leaves your machine. One Rust binary. MIT.
Think of it as an X-ray of your repo that your agent can read: one structure that combines everything and says where each thing lives, what that program is for, what is being worked on, what is done and what is still open. That panorama is the thing no other tool hands your agent.
<p align="center"> <a href="https://www.npmjs.com/package/@maxkle1nz/m1nd"><img src="https://img.shields.io/npm/v/@maxkle1nz/m1nd.svg?color=00f5ff&label=npm" alt="npm" /></a> <a href="https://crates.io/crates/m1nd-mcp"><img src="https://img.shields.io/crates/v/m1nd-mcp.svg?label=crates.io" alt="crates.io" /></a> <a href="https://github.com/maxkle1nz/m1nd/actions"><img src="https://github.com/maxkle1nz/m1nd/actions/workflows/ci.yml/badge.svg" alt="CI" /></a> <a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="License" /></a> <a href="https://registry.modelcontextprotocol.io/?search=io.github.maxkle1nz/m1nd"><img src="https://img.shields.io/badge/MCP_Registry-official-6d28d9" alt="MCP Registry" /></a> </p>
<p align="center">Five commands to install: <a href="#sixty-seconds">Sixty seconds</a>. Reasons to close the tab first: <a href="#when-not-to-use-m1nd">When not to use m1nd</a>.</p>
<p align="center"> <img src="docs/assets/demo.gif" width="760" alt="A real m1nd session: north returns trust, focus and honest gaps; seek answers with a reverify verdict; memorize anchors the finding to code" /> </p>
<p align="center"><em>A real session on this repo's 6,453-node graph (m1nd-mcp 1.4.0): <code>north</code> orients, <code>seek</code> answers wearing a <code>reverify</code> verdict, <code>memorize</code> anchors the finding to code.</em></p>
npx -y @maxkle1nz/m1nd update apply --yes
npx -y @maxkle1nz/m1nd hosts apply --host claude --project . --yes
npx -y @maxkle1nz/m1nd agent first-minute --repo . --query "map this repo" --json ```
Step 4 is the one command only you run. Minting a brain writes a whole graph, so the ceremony has a human terminal ingress and accepts only an empty destination. If an agent finds a repo without a brain, it offers this command and stops. Once the graph exists, the agent can keep it fresh. The ceremony exits non-zero and tells you what to check if the scan finds nothing, so it can never report success over an empty graph.
Step 1 verifies the signature with cosign, so install that first if it is not on your PATH. If you prefer the source registry and accept skipping verification, cargo install m1nd-mcp works too. Prefer to see before you write: hosts plan prints everything hosts apply would touch, and writes nothing. There is no uninstall command yet; hosts plan doubles as the list of what to remove by hand.
The hooks from step 3 are what make m1nd ambient: the orientation packet is injected at every session and subagent spawn, and the agent drives itself from there. Installing from an agent instead of a terminal? There is a machine-legible twin of this section in llms-install.md.
A tampered or truncated release cannot land on your machine, and a bad upgrade is one rollback away: the updater checks the signature against the exact build identity, then the SHA-256 and the size, before it touches anything. If verification fails, it refuses rather than falling back to an unverified path. Details in docs/AGENT-PACKS.md.
Questions your agent can now ask and get a structural answer for:
Each one is a verb on the MCP surface (impact, seek, why, north, ghost_edges, xray_gate, antibody_scan, missing, trust_selftest, predict), not a prompt trick.
高质量的MCP代码图引擎,智能开发辅助
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
总体来看,MCP代码图引擎 是一款质量优秀的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | m1nd |
| 原始描述 | 开源MCP工具:A local code graph engine for MCP agents: proof-aware state, guided next steps, 。⭐20 · Rust |
| Topics | mcpagent-toolsai-agentscode-analysiscode-graph |
| GitHub | https://github.com/maxkle1nz/m1nd |
| License | MIT |
| 语言 | Rust |
收录时间:2026-06-28 · 更新时间:2026-07-04 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端