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MCP server · RAG

Skill2mcp

An innovative approach to decouple MCP tool definitions and encourage federated tool management and governance. Reduce friction between skill design and real-world operations on MCP servers. skill2mcp transforms SKILL.md files into MCP-compatible tools!

Unclaimed last commit 6 months ago rag
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Scored 5 months ago · breakdown

About Skill2mcp

Skill2mcp is an MCP server published by agenttic-ai-dev in the RAG category: an innovative approach to decouple MCP tool definitions and encourage federated tool management and governance. Reduce friction between skill design and real-world operations on MCP servers. skill2mcp transforms SKILL.md files into MCP-compatible tools!.

The repository has 2 stars and 0 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/agenttic-ai-dev/skill2mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

skill2mcp

Language

skill2mcp header

skill2mcp is a TypeScript CLI/library that converts SKILL.md documents into MCP-ready tool definitions and can generate a minimal deployable MCP Server package from a single file or an entire skills directory.

The generated server uses the official MCP TypeScript SDK (@modelcontextprotocol/sdk) and supports stdio, http, or both transports.

Why this project

SKILL documents are usually semi-structured markdown (frontmatter + prose + tables). MCP tools require strict contracts (name, description, inputSchema).

skill2mcp bridges that gap with a layered pipeline:

  1. Parse markdown into a stable Intermediate Representation (IR)
  2. Transform IR into MCP tool definitions
  3. Generate a deployable MCP server package with handler stubs

Current status

MVP implemented and working:

  • Deterministic parser (strict, tolerant)
  • Cascading semantic mode (semantic) for missing metadata fallback
  • Tool transformation (SchemaBuilder, ToolMapper, ToolValidator)
  • inspect output with MCP-style tool JSON
  • build output with deployable MCP server package
  • Generated server supports stdio + http
  • build --watch for iterative regeneration

Installation

Requirements

  • Node.js 20+
  • npm 10+

Local install

npm install

Build CLI

npm run build

Quick start

1. Parse a single SKILL

npm run parse -- ./fixtures/skills/valid-skill.md --mode strict

2. Inspect generated tool definitions

npm run inspect -- ./fixtures/skills --mode tolerant

3. Generate deployable MCP server package

npm run gen -- ./fixtures/skills --out ./generated/mcp-server --transport both --mode tolerant

4. Run generated server

cd ./generated/mcp-server
npm install
npm run build
npm run start:stdio
# or
npm run start:http

HTTP endpoint:

POST /mcp

CLI reference

parse

Converts SKILL markdown to IR JSON.

skill2mcp parse <input> [--mode strict|tolerant|semantic]

Arguments:

  • <input>: path to a .md file or directory

Options:

  • --mode: parser mode (tolerant default)
  • --format: currently json

Output:

  • results[] with parsed SkillDocument
  • diagnostics[] per source file

inspect

Converts parsed IR into MCP-like tool definitions.

skill2mcp inspect <input> [--mode strict|tolerant|semantic]

Output:

  • tools[]: generated tool definitions (name, description, inputSchema)
  • results[]: tool + diagnostics per source

build

Generates a deployable MCP server package from one or many skills.

skill2mcp build <input> --out <dir> [--transport stdio|http|both] [--mode strict|tolerant|semantic] [--watch]

Arguments:

  • <input>: path to a .md file or directory

Required options:

  • --out: output directory for generated package

Optional options:

  • --transport: default generated server transport (both default)
  • --mode: parsing mode (tolerant default)
  • --watch: regenerate package on source changes

Output:

  • generated package files (package.json, tools.json, src/server.ts, handlers)
  • diagnostics summary in JSON

Parse modes

strict

  • Fails on required metadata/schema gaps
  • Best for CI quality gates

tolerant

  • Continues with warnings for missing fields
  • Best for batch processing mixed-quality skills

semantic

  • Starts from tolerant parse
  • Attempts semantic extraction through OpenRouter (when configured)
  • Applies deterministic fallback inference for unresolved fields
  • Keeps diagnostics trace (SEMANTIC_* codes)

OpenRouter configuration for semantic

Environment variables:

  • OPENROUTER_API_KEY: enables remote semantic extraction
  • OPENROUTER_MODEL (optional): defaults to anthropic/claude-3.5-sonnet
  • SKILL2MCP_CACHE_DIR (optional): override cache directory
  • OPENROUTER_HTTP_REFERER (optional): forwarded as OpenRouter header
  • OPENROUTER_X_TITLE (optional): forwarded as OpenRouter header

Cache behavior:

  • Semantic responses are cached by content hash in .skill2mcp-cache/semantic-openrouter-cache.json
  • If cache is present, semantic mode reuses cache and avoids extra remote calls

Canonical SKILL.md format (recommended)

---
name: docx-generator
version: 1.0.0
description: Generate Word docs from structured markdown
tags: [documents, office]
---

## Parameters
| Name | Type | Required | Default | Description |
|------|------|----------|---------|-------------|
| content | string | yes |  | Markdown content |
| title | string | yes |  | Document title |

## Examples
**Input:** `{ content: "# Hello", title: "Report" }`
**Output:** report.docx generated at /outputs/

## Triggers
- "generate document"
- "create report"

Generated package structure

generated/mcp-server/
  package.json
  tsconfig.json
  README.md
  tools.json
  src/
    server.ts
    generated-tools.ts
    handlers/
      index.ts
      <tool_name>.ts

Development

Scripts

npm run build       # compile TypeScript
npm run test        # run test suite
npm run parse       # parse command entry
npm run inspect     # inspect command entry
npm run gen         # build command entry

Test suite

Current automated coverage includes:

  • parser behavior (strict, tolerant, semantic)
  • schema builder and tool mapping
  • inspect command output contract
  • end-to-end build artifact generation

Engineering conventions

  • Follow repository collaboration rules in AGENTS.md
  • Product/business directives are governed by ROADMAP.md
  • Commit messages must use [AI] prefix when AI-generated

Release artifacts

This repo includes:

  • Dual-license distribution: MIT OR Apache-2.0
  • CHANGELOG.md
  • CONTRIBUTING.md
  • RELEASE_CHECKLIST.md

Collaboration model

  • Governance and decision rules: GOVERNANCE.md
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security reporting: SECURITY.md
  • Support channels: SUPPORT.md

Known limitations

  • Parameter parsing currently assumes markdown table format in ## Parameters
  • Semantic mode prioritizes missing metadata and may enrich missing parameters when extraction is available
  • Watch mode tracks current tree; if deeply nested folders are added later, restart watch for complete coverage

Roadmap alignment

The active implementation follows phased delivery in ROADMAP.md.

GenAI integration policy (when enabled) prioritizes OpenRouter as default provider strategy, as defined in roadmap directives.

License

Licensed under either of:

  • MIT License (LICENSE-MIT)
  • Apache License 2.0 (LICENSE-APACHE)

at your option.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Skill2mcp

How do I install Skill2mcp?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Skill2mcp safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Skill2mcp still maintained?

The last commit was 6 months ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.