Bodhi MCP

菩提MCP

人工智能代理的综合决策框架。通过精心策划的知识获得启蒙。

菩提是什么？

Bodhi是一个MCP（模型上下文协议）服务器，它提供 预合成知识 人工智能代理无法自行推导——决策框架需要2个以上的来源和人类的判断。

与原始文档不同，Bodhi提供 提炼的智慧：从多个权威来源综合的决策指南、常见错误和可操作的清单。

快速开始

MCP兼容客户端（克劳德桌面、光标等）

添加到您的MCP客户端配置中（例如。， claude_desktop_config.json):

{
  "mcpServers": {
    "bodhi": {
      "command": "npx",
      "args": ["bodhi-mcp"]
    }
  }
}

或者使用自定义知识路径：

{
  "mcpServers": {
    "bodhi": {
      "command": "npx",
      "args": ["bodhi-mcp", "--knowledge-path", "/path/to/your/knowledge-base"]
    }
  }
}

本地开发

# Clone and install
git clone https://github.com/5h1vmani/bodhi-mcp.git
cd bodhi-mcp
npm install

# Build
npm run build

# Run with your knowledge base
npm start -- --knowledge-path /path/to/nucleus

可用工具

所有工具都使用 bodhi_ 前缀，返回markdown和结构化JSON(response_format: "json" | "markdown")，并包括 outputSchema + annotations.

bodhi_route(task)

为给定任务找到最佳剧本。

使用INDEX.md路由表将任务与相关剧本相匹配。返回最相关的剧本，包括置信度得分和备选方案。

Input: { "task": "pitch deck design for investors" }
Output: {
  "playbook": "domains/marketing/pitch-deck-strategy.md",
  "confidence": 0.85,
  "title": "Pitch Deck Strategy",
  "domain": "marketing",
  "tldr": "Stage-specific structure, investor psychology...",
  "alternatives": [...]
}

bodhi_search(query, domain?, limit?)

在所有剧本中进行全文搜索。

用于更广泛的查询 bodhi_route() 找不到匹配项，或探索相关主题。

Input: { "query": "UPI payment", "domain": "ux" }
Output: [
  { "path": "domains/ux/india-checkout-patterns.md", "title": "India Checkout Patterns", "score": 12.5, ... },
  ...
]

bodhi_list(domain?, complexity?, limit?)

列出所有可用的带有元数据的剧本。

用于探索可用的知识或按领域/复杂性过滤。

Input: { "domain": "security", "complexity": "advanced" }
Output: [
  { "path": "domains/security/serverless-aws-security.md", "title": "Serverless AWS Security", ... },
  ...
]

bodhi_read(path, section?)

阅读特定剧本的完整内容。

使用后 bodhi_route() 或 bodhi_search() 获取完整的剧本内容。

Input: { "path": "domains/ux/gamification.md", "section": "Decision Guide" }
Output: "## Decision Guide\n\n| Scenario | Approach | Why |..."

bodhi_summary()

获取知识库的摘要。

返回总剧本、域和复杂性分布。

bodhi_diagnose()

健康检查和调试信息。

用于解决安装问题或验证知识库是否正确加载。

Output: {
  "status": "healthy",
  "version": "0.3.0",
  "playbooksCount": 82,
  "routesCount": 246,
  "domainsFound": ["ux", "marketing", "security", ...],
  "issues": [],
  "recommendations": []
}

领域

菩提将知识组织到各个领域：

MCP规范合规性（v0.3.0）

创建自己的知识库

Bodhi使用遵循Nucleus格式的任何知识库：

knowledge/
├── INDEX.md              # Task routing table
├── domains/
│   ├── ux/
│   │   ├── _index.md     # Domain index
│   │   ├── gamification.md
│   │   └── ...
│   ├── marketing/
│   │   └── ...
│   └── ...
└── meta/
    └── contributing.md   # Contribution guidelines

剧本格式

每个剧本都遵循一种标准格式：

---
domain: ux
topic: gamification
tags: [engagement, retention, psychology]
complexity: intermediate
last_updated: 2025-01-15
confidence: 0.85
status: validated
review_by: 2025-07-01
---

# Gamification

> One-line value proposition.

## TL;DR

- **Key insight 1** — supporting detail
- **Key insight 2** — supporting detail

## Decision Guide

| Scenario | Approach | Why |
|----------|----------|-----|
| Specific situation | Concrete recommendation | Reasoning |

## Common Mistakes

| Mistake | Fix |
|---------|-----|
| Real failure | Specific solution |

## Checklist

- [ ] Verification item 1
- [ ] Verification item 2

INDEX.md路由表

路由表将任务映射到剧本：

## Task Routing

| Task | Read This |
|------|-----------|
| Gamification | `domains/ux/gamification.md` |
| Pitch deck design | `domains/marketing/pitch-deck-strategy.md` |

环境变量

发展

# Install dependencies
npm install

# Build
npm run build

# Run tests
npm test

# Lint
npm run lint

# Type check
npm run typecheck

承诺公约

此项目使用 常规承诺提交消息通过commitlist进行验证。

: 

# Examples:
feat: add new search filter option
fix: resolve routing table parsing error
docs: update installation instructions
chore: upgrade dependencies

类型： feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert

许可证

麻省理工学院

贡献

1. 克隆该仓库
2. 创建功能分支(git checkout -b feature/amazing-feature)
3. 提交您的更改(git commit -m 'feat: add amazing feature')
4. 推到分支(git push origin feature/amazing-feature)
5. 打开拉取请求

______________________________________________________________________

内置于❤️ 通过 菩提团队 对于寻求启示的人工智能代理。