mcp-code-execution-enhanced

🥈Silver

Enhanced MCP code execution reduces token usage by 99.6% for operations teams. CLI-based scripts and progressive tool discovery optimize Model Context Protocol servers. Works with any agent framework, optimized for Claude Code.

4030Updated 2w ago

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/yoloshii/mcp-code-execution-enhanced.git

Works with:

Claude

Overview

About This Skill

How to Use

1. **Prepare your environment**: Ensure MCP-Code-Enhanced is installed in your agent framework (e.g., `pip install mcp-code-execution-enhanced`). For Claude Code, verify integration via `claude --list-tools`. 2. **Specify your target**: Replace [SERVER_NAME], [PLATFORM], and [FRAMEWORK] in the prompt template with your actual system (e.g., 'auth-service' on AWS ECS with FastAPI). 3. **Run the analysis**: Paste the prompt into your AI tool and execute. The script will auto-discover available tools (e.g., `kubectl`, `docker`, `node --inspect`). 4. **Validate outputs**: Review the generated script and metrics. Use the rollback plan if needed. For complex systems, run the script in a staging environment first. 5. **Monitor improvements**: Track the before/after metrics in your observability dashboard (e.g., Prometheus, Datadog). Adjust the CLI flags if performance degrades under load. *Tip: For maximum efficiency, pre-load your MCP server with common tools (e.g., `kubectl`, `jq`) to reduce discovery time by 60%.*

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/yoloshii/mcp-code-execution-enhanced

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

Use MCP-Code-Execution-Enhanced to analyze and optimize the performance of [SERVER_NAME] running on [PLATFORM] with [FRAMEWORK]. Identify the top 3 bottlenecks in [SPECIFIC_AREA] and generate a CLI-based script to resolve them. Include progressive tool discovery to validate the changes. Output should include before/after metrics and a rollback plan if issues arise.

Example Output

### Performance Analysis for 'api-gateway-prod' on Kubernetes (Claude Code v1.0)

**Current State:**
- Avg. response time: 420ms (P95: 850ms)
- Memory leaks detected in /api/v2/analytics endpoint (3.2MB/min growth)
- CPU throttling observed during traffic spikes (40% above baseline)

**Optimization Script (Generated via MCP-Code-Execution-Enhanced):**
```bash
#!/bin/bash
# Progressive tool discovery enabled
kubectl exec -it api-gateway-prod-abc123 -- /bin/sh -c "
echo '=== Memory Leak Fix ==='
# Patch Node.js GC settings
kubectl set env deployment/api-gateway-prod NODE_OPTIONS='--max-old-space-size=512 --gc-global'

# Validate memory improvement
echo '=== Validation ==='
kubectl exec -it api-gateway-prod-abc123 -- /bin/sh -c "
  node -e \"console.log('Heap after fix:', process.memoryUsage().heapUsed/1024/1024 + 'MB')\"
"
"
```

**Results After Implementation:**
- Avg. response time: 180ms (P95: 320ms) → **57% improvement**
- Memory growth stabilized at 0.1MB/min
- CPU usage during spikes reduced to 15% above baseline

**Rollback Plan:**
```bash
kubectl rollout undo deployment/api-gateway-prod
```

*Generated with 99.6% token efficiency vs. traditional methods. Progressive tools validated changes in 2.1s (vs. 45s manual checks).*