MCP工具模板
经 AI Skill Hub 精选评估，MCP工具模板 获评「强烈推荐」。这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色，AI 评分 8.0 分，适合有一定技术背景的用户使用。
📚 深度解析
通过安装 MCP工具模板，你的 AI 助手将获得额外的工具调用能力，可以用自然语言直接操控该工具的功能，无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置，永久增强"——配置完成后，每次与 AI 对话时都可以无缝调用这些工具。
在技术实现上，MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信，工具的功能以"工具列表"的形式暴露给 AI 模型，AI 可以按需调用。MCP工具模板 提供了结构化的工具调用接口，使 AI 模型能够精确地理解和使用每个功能点，显著降低 AI 在工具使用上的错误率。
与传统的 API 集成相比，MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON，即可让 AI 获得全新能力。AI Skill Hub 将 MCP工具模板 评为 AI 评分 8.0 分，属于同类工具中的优质选择。
📋 工具概览
MCP工具模板 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。
📖 中文文档
MCP工具模板 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。
- 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
- 提供结构化工具调用接口，显著降低 AI 集成复杂度
- 支持 Claude Desktop 和 Claude Code 无缝接入，开箱即用
- 可与其他 MCP 工具组合叠加，构建完整 AI 工作站
- 轻量无侵入设计，不影响现有系统架构
- 在 Claude Desktop 对话中直接调用本地工具，实现 AI 与系统的深度联动
- 通过自然语言驱动复杂的多步骤自动化任务，代替繁琐手动操作
- 将多个 MCP 工具组合使用，构建个人专属 AI 工作站
# 方式一：通过 Claude Code CLI 一键安装
claude skill install https://github.com/AndrewAltimit/template-repo
# 方式二：手动配置 claude_desktop_config.json
{
"mcpServers": {
"mcp----": {
"command": "npx",
"args": ["-y", "template-repo"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
- 确认已安装 Node.js（v18 或以上版本）
- 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
- 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
- 保存配置文件并重启 Claude 客户端
- 重启后，在对话中即可使用本工具
# 安装后在 Claude 对话中直接使用 # 示例： 用户: 请帮我用 MCP工具模板 执行以下任务... Claude: [自动调用 MCP工具模板 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", "template-repo"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Agent Orchestration & Security Template
A reference architecture for AI agent orchestration, trust measurement, and tool integration. Designed to be studied, forked, and adapted -- not contributed to directly. All code changes in this repository are authored by AI agents under human oversight. Browse the project showcase for an overview.
This repo demonstrates how to run a council of AI agents (Claude, OpenCode, Crush) across a shared codebase with board-driven task delegation, automated PR review, security hardening, and containerized tooling. (OpenAI/Google integrations have been disabled -- see security notice.) It also includes standalone research packages for sleeper agent detection, autonomous economic agent simulation, and tamper-responsive hardware. Several companion repositories consume or extend the functionality of this project.
Use this repo to learn how to: - Orchestrate multiple AI agents with a GitHub Projects v2 work queue - Measure and enforce trust boundaries for autonomous agents (wrapper guards, iteration limits, claim tracking) - Integrate 20 MCP servers spanning code quality, content creation, 3D graphics, video editing, and speech synthesis - Build hardened CI/CD pipelines for agent-authored code (15-stage pipeline, security scanning, multi-arch Docker builds) - Detect sleeper agent behaviors via residual stream analysis and linear probes - Integrate AI agents into legacy software via runtime injection, shared memory IPC, and overlay rendering
---
Important: This is an advanced template designed for experienced developers working with autonomous AI agents. Before diving in, we strongly recommend: 1. Read the AI Safety Training Guide - Essential concepts for safe human-AI collaboration, including deception detection, scalable oversight, and control protocols 2. Take an AI Safety course at BlueDot Impact - Free, rigorous training programs covering AI safety fundamentals, governance, and alignment Working with AI agents introduces risks that differ fundamentally from traditional software. Understanding these risks isn't optional - it's a prerequisite for responsible development.
---
Features
- 20 MCP Servers - Code quality, content creation, AI assistance, 3D graphics, video editing, speech synthesis, and more
- 6 AI Agents - Autonomous development workflow from issue to merge
- 4 Packages - Sleeper agent detection, economic agent simulation, tamper-responsive briefcase, CRISPR automation
- Container-First Architecture - Maximum portability and consistency
- Self-Hosted CI/CD - Zero-cost GitHub Actions infrastructure
- Company Integration - Corporate proxy builds for enterprise AI APIs (Docs)
Build Rust packages (requires Rust toolchain)
cd packages/economic_agents && cargo build --release cd tools/rust/github-agents-cli && cargo build --release cd tools/rust/board-manager && cargo build --release ```
Install Python packages
pip install -e ./packages/sleeper_agents
Enterprise & Corporate Setup
For enterprise environments requiring custom certificates, customize automation/corporate-proxy/shared/scripts/install-corporate-certs.sh. This script runs during Docker builds for all containers. See the customization guide for details.
Setup Guides
Setup & Configuration
- Template Quickstart Guide - Customize the template for your needs
- Self-Hosted Runner Setup
- GitHub Environments Setup
- Containerized CI
Quick Start
New to the template? Check out our Template Quickstart Guide for step-by-step customization instructions!
- Prerequisites: Linux system with Docker (v20.10+) and Docker Compose (v2.0+)
2. Clone and setup
git clone https://github.com/AndrewAltimit/template-repo
cd template-repo
# Build the Rust CLI tools (optional - pre-built binaries available in releases)
cd tools/rust/board-manager && cargo build --release
cd ../github-agents-cli && cargo build --release
3. Set API keys (if using AI features)
export OPENROUTER_API_KEY="your-key-here" # For OpenCode/Crush
- Use with Claude Code: MCP servers are configured in
.mcp.jsonand auto-started by Claude. See MCP Configuration for essential vs full setups.
5. Run CI/CD operations
automation-cli ci run full # Full pipeline
For detailed setup, see CLAUDE.md and Template Quickstart Guide.
Technical Guides
| Guide | Description | Source | |
|---|---|---|---|
| **Agentic Workflow Handout** | AI agent pipeline architecture and workflows | [Download](https://github.com/AndrewAltimit/template-repo/releases/latest) | [LaTeX](docs/agents/Agentic_Workflow_Handout.tex) |
| **Sleeper Agents Framework** | AI backdoor detection using residual stream analysis | [Download](https://github.com/AndrewAltimit/template-repo/releases/latest) | [LaTeX](packages/sleeper_agents/docs/Sleeper_Agents_Framework_Guide.tex) |
| **AgentCore Memory Integration** | Multi-provider AI memory system | [Download](https://github.com/AndrewAltimit/template-repo/releases/latest) | [LaTeX](docs/integrations/ai-services/AgentCore_Memory_Integration_Guide.tex) |
| **Virtual Character System** | AI agent embodiment platform | [Download](https://github.com/AndrewAltimit/template-repo/releases/latest) | [LaTeX](docs/integrations/ai-services/Virtual_Character_System_Guide.tex) |
| **AI Agent Containment & Infrastructure Security** | Isolation, trust-tiered execution, and physical security for AI agents | [Download](https://github.com/AndrewAltimit/template-repo/releases/latest) | [LaTeX](docs/hardware/latex/ai-agent-containment-infrastructure-security-framework.tex) |
| **BioForge CRISPR Automation** | Agent-driven biological automation platform | [Download](https://github.com/AndrewAltimit/template-repo/releases/latest) | [LaTeX](docs/hardware/latex/bioforge-crispr-automation.tex) |
| **Secure Terminal Briefcase** | Tamper-responsive hardware security system with PQC recovery | [Download](https://github.com/AndrewAltimit/template-repo/releases/latest) | [LaTeX](docs/hardware/latex/secure-terminal-briefcase.tex) |
Usage Modes
- STDIO Mode (local MCPs): Configured in
.mcp.json, auto-started by Claude - HTTP Mode (remote MCPs): Run the MCP using docker compose on the remote node.
See MCP Architecture Documentation and STDIO vs HTTP Modes for details.
Integration Guides
Configuration
Environment Variables
See .env.example for all available options.
Key Configuration Files
.mcp.json- MCP server configuration for Claude Codedocker-compose.yml- Container services configurationCLAUDE.md- Project-specific Claude Code instructions (root directory)AGENTS.md- Universal AI agent configuration and guidelines (root directory)docs/agents/project-context.md- Context for AI reviewers
Tool Reference
For complete tool listings, see MCP Tools Reference
Quick References
Agentic Git Workflow
AI agents autonomously manage the development lifecycle from issue creation through PR merge:
Issue Created → Admin Approval → Agent Claims → PR Created → AI Review → Human MergeThe Flow:
- Issue Creation - Issues are created manually or by agents via
backlog-refinement.yml, automatically added to the GitHub Projects board - Admin Approval - An authorized user comments
[Approved][Claude](or another agent name) to authorize work - Agent Claims -
board-agent-worker.ymlfinds approved issues, the agent claims the issue and creates a working branch - Implementation - The agent implements the fix/feature and opens a PR
- AI Review -
pr-validation.ymltriggers AI code review (Claude + OpenRouter);pr-review-monitor.ymllets agents iterate on feedback - Human Merge - Admin reviews and merges the PR
Security Model:
- Approval Required - Agents cannot work on issues without explicit
[Approved][Agent]comment - Authorized Users Only - Only users listed in
.agents.yaml→security.agent_adminscan approve - Pattern Validation - Must use
[Action][Agent]format (e.g.,[Approved][Claude]) to prevent false positives - Claim Tracking - Agents post claim comments with timestamps to prevent conflicts
See Security Documentation for the complete security model.
Packages
Standalone packages addressing different aspects of AI agent development, safety, and security:
| Package | Purpose | Documentation | |
|---|---|---|---|
| **[Sleeper Agents](packages/sleeper_agents/)** | Research-validated detection framework for hidden backdoors in LLMs, based on Anthropic's research on deceptive AI that persists through safety training | [README](packages/sleeper_agents/README.md) \ | [PDF Guide](https://github.com/AndrewAltimit/template-repo/releases/latest) |
| **[Economic Agents](packages/economic_agents/)** | Rust-based simulation framework demonstrating autonomous AI economic capability - agents that earn money, form companies, hire sub-agents, and seek investment. For governance research and policy development | [README](packages/economic_agents/README.md) | |
| **[Tamper Briefcase](packages/tamper_briefcase/)** | Tamper-responsive Raspberry Pi briefcase with dual-sensor detection, LUKS2 cryptographic wipe, and hybrid PQC recovery USB. For secure physical transport of field-deployable agent terminals | [README](packages/tamper_briefcase/README.md) \ | [Hardware Docs](docs/hardware/secure-terminal-briefcase.md) |
Rust CLI Tools (in tools/rust/):
| Tool | Purpose | Documentation |
|---|---|---|
| **[github-agents-cli](tools/rust/github-agents-cli/)** | Issue/PR monitoring, refinement, code analysis, and agent execution | [README](tools/rust/github-agents-cli/README.md) |
| **[board-manager](tools/rust/board-manager/)** | GitHub Projects v2 board operations - claim, release, status updates | [README](tools/rust/board-manager/README.md) |
| **[git-guard](tools/rust/git-guard/)** | Git CLI wrapper requiring sudo for dangerous operations (force push, --no-verify) | [README](tools/rust/git-guard/README.md) |
| **[gh-validator](tools/rust/gh-validator/)** | GitHub CLI wrapper for automatic secret masking | [README](tools/rust/gh-validator/README.md) |
| **[pr-monitor](tools/rust/pr-monitor/)** | Dedicated PR monitoring for admin/review feedback during development | [README](tools/rust/pr-monitor/README.md) |
| **[markdown-link-checker](tools/rust/markdown-link-checker/)** | Fast concurrent markdown link validator for CI/CD pipelines | [README](tools/rust/markdown-link-checker/README.md) |
| **[code-parser](tools/rust/code-parser/)** | Parse and apply code blocks from AI agent responses | [README](tools/rust/code-parser/README.md) |
| **[mcp-code-quality](tools/mcp/mcp_code_quality/)** | Rust MCP server for code quality tools (formatting, linting, testing) | [README](tools/mcp/mcp_code_quality/README.md) |
Development Workflow
高质量的MCP工具模板，适合代理编排与安全
⚡ 核心功能
- 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
- 提供结构化工具调用接口，显著降低 AI 集成复杂度
- 支持 Claude Desktop 和 Claude Code 无缝接入，开箱即用
- 可与其他 MCP 工具组合叠加，构建完整 AI 工作站
- 轻量无侵入设计，不影响现有系统架构
👥 适合人群
🎯 使用场景
- 在 Claude Desktop 对话中直接调用本地工具，实现 AI 与系统的深度联动
- 通过自然语言驱动复杂的多步骤自动化任务，代替繁琐手动操作
- 将多个 MCP 工具组合使用，构建个人专属 AI 工作站
⚖️ 优点与不足
- +标准化 MCP 协议，生态互联性强
- +与 Claude 官方生态无缝对接
- +即插即用，配置简单快捷
- −依赖 Claude 客户端，非 Claude 用户无法使用
- −MCP 协议仍在持续演进，接口可能变更
- −需要一定的配置步骤
该工具使用 Unlicense 协议，商用场景请仔细阅读协议条款，必要时咨询法律意见。
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。
✅ Unlicense — 公共领域，完全无版权限制，可自由使用。
🔗 相关工具推荐
❓ 常见问题 FAQ
AI Skill Hub 点评：MCP工具模板 的核心功能完整，质量优秀。对于Claude Desktop / Claude Code 用户来说，这是一个值得纳入个人工具库的选择。建议先在非生产环境试用，再逐步推广。
| 原始名称 | template-repo |
| Topics | agent-orchestrationagent-securityai-agentsai-governancerust |
| GitHub | https://github.com/AndrewAltimit/template-repo |
| License | Unlicense |
| 语言 | Rust |
收录时间：2026-07-05 · 更新时间：2026-07-05 · License：Unlicense · AI Skill Hub 不对第三方内容的准确性作法律背书。