skill-to-mcp

🥈Silver

Converts AI skills from Claude Skills format to MCP server resources. Enables biomedical researchers and developers to integrate AI skills into their workflows. Connects to BioContextAI's registry and MCP servers for deployment.

1740Updated 1w ago

Intermediate30min to implementautomation

Saves ~60 min per use

Quick InstallView Source

git clone https://github.com/biocontext-ai/skill-to-mcp.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/biocontext-ai/skill-to-mcp

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Convert the following AI skill from Claude Skills format to MCP server resources: [SKILL_NAME]. Ensure compatibility with BioContextAI's registry and MCP servers. Include all necessary metadata and dependencies. [SKILL_DESCRIPTION]

Example Output

# MCP Server Resource Conversion

## Skill Name: Drug Interaction Analyzer

## Description
Converts and analyzes potential drug interactions based on patient data and medical history.

## Metadata
- **Category**: Biomedical Analysis
- **Input Type**: Text (Patient Data, Medical History)
- **Output Type**: Text (Drug Interaction Analysis)
- **Dependencies**: BioContextAI Registry, MCP Servers

## Conversion Details
- **Input Format**: JSON
- **Output Format**: JSON
- **API Endpoint**: `/api/v1/drug_interaction_analyzer`

## Example Input
```json
{
  "patient_data": {
    "age": 65,
    "gender": "male",
    "medical_history": ["hypertension", "diabetes"],
    "current_medications": ["lisinopril", "metformin"]
  }
}
```

## Example Output
```json
{
  "interactions": [
    {
      "drug1": "lisinopril",
      "drug2": "metformin",
      "severity": "low",
      "description": "No significant interactions expected."
    },
    {
      "drug1": "lisinopril",
      "drug2": "aspirin",
      "severity": "moderate",
      "description": "Monitor for signs of hyperkalemia."
    }
  ]
}
```