Skill-MCP is a powerful LLM-managed skills platform that allows users to create, edit, and execute skills programmatically across various MCP-compatible clients like Claude and Cursor, streamlining the development process without manual uploads.
claude install fkesheh/skill-mcpSkill-MCP is a powerful LLM-managed skills platform that allows users to create, edit, and execute skills programmatically across various MCP-compatible clients like Claude and Cursor, streamlining the development process without manual uploads.
Automating skill creation for AI agents
Integrating skills into existing workflows
Enhancing AI capabilities without manual intervention
Rapid prototyping of AI functionalities
claude install fkesheh/skill-mcpgit clone https://github.com/fkesheh/skill-mcpCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create a new skill for Skill-MCP that automates [TASK] for [COMPANY] in the [INDUSTRY] sector. The skill should use [DATA] and integrate with [TOOLS]. Provide the code and a brief explanation of how it works.
```python
# Skill-MCP Automated Task Manager
# Task: Automate customer feedback analysis for TechSolutions Inc. in the IT sector
# Data: Customer feedback CSV files
# Tools: Python, Pandas, NLP libraries
import pandas as pd
from textblob import TextBlob
def analyze_feedback(file_path):
# Load data
df = pd.read_csv(file_path)
# Analyze sentiment
df['sentiment'] = df['feedback'].apply(lambda x: TextBlob(x).sentiment.polarity)
# Categorize feedback
df['category'] = df['feedback'].apply(lambda x: 'positive' if TextBlob(x).sentiment.polarity > 0 else 'negative' if TextBlob(x).sentiment.polarity < 0 else 'neutral')
return df
# Usage
feedback_data = analyze_feedback('customer_feedback.csv')
print(feedback_data.head())
```
This skill automates the analysis of customer feedback for TechSolutions Inc. It uses Pandas to load and manipulate the data, and TextBlob for sentiment analysis. The skill categorizes feedback as positive, negative, or neutral based on sentiment polarity.Take a free 3-minute scan and get personalized AI skill recommendations.
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