skill-forge-mcp

skill-forge-mcp

An MCP server that exposes the Agent Skill creation guide (9 phases) as MCP resources, enabling AI agents to build SKILL.md files on demand.

Category
访问服务器

README

<p align="center"> <a href="https://www.npmjs.com/package/skill-forge-mcp"><img src="https://img.shields.io/npm/v/skill-forge-mcp.svg" alt="npm version"></a> <a href="https://github.com/popyson1648/skill-forge-mcp/actions/workflows/ci.yml"><img src="https://github.com/popyson1648/skill-forge-mcp/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: MIT"></a> </p>

<p align="center"> <img src="docs/images/logo.png" alt="SkillForge MCP" width="480"> </p>

日本語

An MCP server that exposes the Agent Skill creation guide (9 phases) as MCP resources. AI agents retrieve only the phases they need on demand and follow the process to build SKILL.md files.

Quick Start

Claude Code:

claude mcp add skill-forge-mcp -- npx skill-forge-mcp

Gemini CLI:

gemini mcp add skill-forge-mcp -- npx skill-forge-mcp

VS Code (GitHub Copilot).vscode/mcp.json:

{
  "servers": {
    "skill-forge-mcp": {
      "command": "npx",
      "args": ["skill-forge-mcp"]
    }
  }
}

Cursor:

{
  "skill-forge-mcp": {
    "command": "npx",
    "args": ["skill-forge-mcp"]
  }
}

<details> <summary>Claude Desktop</summary>

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

</details>

Usage

Ask your agent:

"I want to create a skill for React component design. Follow the SkillForge MCP process."

The agent will automatically:

  1. Fetch the process structure from process://manifest
  2. Read Phase 1 (process://phase/1) for scoping, run baseline measurements
  3. Record progress with mark_progress as it advances through each phase
  4. Generate the final SKILL.md following Phase 6 guidelines

Use search_process for keyword lookups across phases.

The 9 Phases

Phase Name Purpose
0 Skill Specification SKILL.md structure and frontmatter
1 Scoping & Baseline Measure failure patterns; define research scope
2 Domain Research Establish quality criteria and theoretical foundations
3 Gap Analysis Verify whether research alone enables the agent to act
4 Deep Implementation Research Fill gaps with code examples, anti-patterns, validation
5 Structuring & Completeness Confirm coverage across all categories
6 Distillation into SKILL.md Condense into ≤500 lines; maximize token efficiency
7 Deploy & Validate Place, verify spec compliance, security review
8 Evaluate & Iterate Compare against baseline, improve iteratively

Features

  • Staged access — retrieve content at phase or section granularity
  • Cross-phase search — keyword search across all 9 phases
  • Progress tracking — record and query per-phase completion status
  • Prompt templatescreate_skill and resume_skill prompts for guided workflows
  • Structured outputoutputSchema + structuredContent on all tools for programmatic consumption
  • State persistence — optionally retain progress across sessions
  • Low overhead — ~1,500 token fixed cost to the context window

API

Resources

URI Description
process://manifest Full index (JSON)
process://phase/0process://phase/8 Phase 0–8 content

Resource Templates

Template Description
process://phase/{phaseId}/section/{sectionName} Retrieve a single section
process://phases/{+phaseIds} Batch retrieval (e.g. 1,2,3)

Tools

Tool Description Input
search_process Keyword search across all phases { "query": "frontmatter", "maxResults": 5 }
mark_progress Record phase progress { "phaseId": 1, "status": "in-progress" }
get_status Progress summary for all phases {}

status: "not-started" · "in-progress" · "completed"

Prompts

Prompt Description
create_skill Full guided workflow (Phase 0→8). Accepts a topic argument.
resume_skill Resume from current progress. Checks get_status and continues.

Configuration

Set SKILL_FORGE_PERSIST=true to persist progress to ~/.skill-forge-mcp/state.json:

{
  "mcpServers": {
    "skill-forge-mcp": {
      "command": "npx",
      "args": ["skill-forge-mcp"],
      "env": { "SKILL_FORGE_PERSIST": "true" }
    }
  }
}

Development

git clone https://github.com/popyson1648/skill-forge-mcp.git
cd skill-forge-mcp
npm install
npm run build
npm test          # 52 tests

<details> <summary>Project structure</summary>

src/
├── index.ts        # Entry point
├── content.ts      # Content loading & section extraction
├── search.ts       # Cross-phase search
├── state.ts        # State management & persistence
├── status.ts       # Status table formatter
├── content/        # English content (served)
└── content-ja/     # Japanese translations (developer reference only)
tests/
├── content.test.ts
├── search.test.ts
├── state.test.ts
├── resources.test.ts
└── tools.test.ts

</details>

Requirements: Node.js >= 18

Contributing

Contributions are welcome! Feel free to open an Issue or submit a Pull Request.

License

MIT

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