aman-mcp

aman-mcp

Exposes identity, tools, workflows, guardrails, and evaluation as MCP tools — so any AI agent can read and write your ecosystem programmatically.

Category
访问服务器

README

<div align="center">

<br>

<picture> <source media="(prefers-color-scheme: dark)" srcset="https://img.shields.io/badge/aman--mcp-MCP_server-white?style=for-the-badge&labelColor=0d1117&color=58a6ff"> <img alt="aman-mcp" src="https://img.shields.io/badge/aman--mcp-MCP_server-black?style=for-the-badge&labelColor=f6f8fa&color=24292f"> </picture>

The MCP server for the aman ecosystem.

Exposes identity, tools, workflows, guardrails, and evaluation as MCP tools — so any AI agent can read and write your ecosystem programmatically.

<br>

npm CI License: MIT MCP aman

Setup · Tools · Architecture · Ecosystem

</div>


How It Works

┌─────────────────────────────────────────────┐
│              AI Agent / LLM                 │
│         (Claude, GPT, Cursor, etc.)         │
└──────────────────┬──────────────────────────┘
                   │ MCP Protocol
        ┌──────────┴──────────┐
        │     aman-mcp        │  ← this server
        │  11 tools across    │
        │  5 ecosystem layers │
        └──┬──┬──┬──┬──┬─────┘
           │  │  │  │  │
     ┌─────┘  │  │  │  └─────┐
     ▼        ▼  ▼  ▼        ▼
  acore    akit aflow arules aeval
 identity tools flows guards  eval

amem (memory) runs as its own MCP server — see amem.


Setup

<details> <summary><strong>Claude Code</strong></summary>

One-liner:

claude mcp add aman -- npx -y @aman_asmuei/aman-mcp

Or manually add to ~/.claude/settings.json:

{
  "mcpServers": {
    "aman": {
      "command": "npx",
      "args": ["-y", "@aman_asmuei/aman-mcp"]
    }
  }
}

</details>

<details> <summary><strong>Cursor</strong></summary>

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "aman": {
      "command": "npx",
      "args": ["-y", "@aman_asmuei/aman-mcp"]
    }
  }
}

</details>

<details> <summary><strong>Windsurf</strong></summary>

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "aman": {
      "command": "npx",
      "args": ["-y", "@aman_asmuei/aman-mcp"]
    }
  }
}

</details>

<details> <summary><strong>Any other MCP client</strong></summary>

aman-mcp speaks standard Model Context Protocol over stdio:

npx @aman_asmuei/aman-mcp

</details>


Tools

Identity (acore) — ~/.acore/core.md

Tool Description
identity_read Read the full core.md identity file
identity_summary Get structured summary: AI name, user name, trust level, personality
identity_update_session Update the Session section (resume, topics, decisions)

Tools (akit) — ~/.akit/kit.md

Tool Description
tools_list List all installed tools with status
tools_search Search tool registry by query

Workflows (aflow) — ~/.aflow/flow.md

Tool Description
workflow_list List all defined workflows
workflow_get Get a specific workflow's steps

Guardrails (arules) — ~/.arules/rules.md

Tool Description
rules_list List all rule categories
rules_check Check if an action violates any rules

Evaluation (aeval) — ~/.aeval/eval.md

Tool Description
eval_status Get evaluation metrics (sessions, trust, trajectory)
eval_log Log a session with rating and notes

Projects (aprojects) — LRU work-thread tracker

Discrete arcs of work, LRU-positioned across 10 active slots, peer to intentions / eval / rules. Active project surfaces unconditionally in SessionStart.

Storage: ~/.aprojects/dev/plugin/projects.md (single file via MarkdownFileStorage; matches intentions pattern).

Tools:

  • project_add — create at #1, shift others, evict at #11
  • project_get — read one
  • project_list — filter by status / inActiveList
  • project_active — fast path: position #1
  • project_load — fuzzy match, restore from off-list
  • project_touch — bump in-list project to #1
  • project_save — append timestamped session note
  • project_close — transition to complete / paused / abandoned
  • project_update — patch metadata; reciprocally updates intentions.linkedProjectId

Lifecycle vs LRU: orthogonal axes. status is lifecycle (active/paused/complete/abandoned). inActiveList is LRU membership. LRU eviction at #11 sets inActiveList=false but keeps status=active — the project is still alive, just not in the top 10.

Bidirectional link: Setting linkedIntentionId on a project also sets linkedProjectId on the intention (and vice versa). Closing one side does NOT close the other.

Override paths root: $AMAN_PROJECTS_HOME (used by tests).


Architecture

src/
├── index.ts        Entry point — server setup, transport
├── tools/          MCP tool definitions per layer
├── parsers/        Markdown file parsers
└── utils/          Shared utilities

File Locations

The server reads and writes the same files as the CLI tools:

File Layer
~/.acore/core.md Identity and personality
~/.akit/kit.md Tool registry
~/.aflow/flow.md Workflow definitions
~/.arules/rules.md Guardrail rules
~/.aeval/eval.md Evaluation log

Development

git clone https://github.com/amanasmuei/aman-mcp.git
cd aman-mcp
npm install
npm run build
npm run lint
npm test

The Ecosystem

aman
├── acore      → identity    → who your AI IS
├── amem       → memory      → what your AI KNOWS
├── akit       → tools       → what your AI CAN DO
├── aflow      → workflows   → HOW your AI works
├── arules     → guardrails  → what your AI WON'T do
├── aeval      → evaluation  → how GOOD your AI is
└── aman-mcp   → MCP server  → the bridge  ← YOU ARE HERE
Layer Package What it does
Identity acore Personality, values, relationship memory
Memory amem Automated knowledge storage (MCP)
Tools akit 15 portable AI tools (MCP + manual fallback)
Workflows aflow Reusable AI workflows
Guardrails arules Safety boundaries and permissions
Evaluation aeval Relationship tracking and session logging
Unified aman One command to set up everything

Contributing

Contributions welcome! Open an issue or submit a PR.

License

MIT


<div align="center">

11 tools. 5 layers. One MCP server.

</div>

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选