| name | mcp-standards |
| description | Use when developing MCP servers to access comprehensive standards for scaffolding, packaging, sampling, documentation, testing, error handling, monitoring, and CI/CD workflows. |
MCP Standards - Complete Reference
The comprehensive standards collection for the MCP (Model Context Protocol) ecosystem. This skill provides access to all MCP standards documentation, from initial scaffolding to production deployment.
When to Use This Skill
Use this skill for:
- MCP server development and standards compliance
- FastMCP version requirements and migration
- Repository structure and project setup
- Documentation standards and practices
- Testing, error handling, and monitoring standards
- CI/CD workflows and deployment patterns
Don't use for:
- General programming questions
- Non-MCP specific development
- Individual coding problems
Standards Categories
🚀 Development Standards
🎨 Frontend & Integration
🛠️ DevOps & Quality
📖 Documentation & Process
Key Requirements
FastMCP Version
Minimum: FastMCP 2.14.3+ - Required for sampling support and enhanced AI workflows.
Status Classification
- ✅ Tested and Working - Verified functionality with tests
- 🟡 Implemented but Untested - Code complete, testing needed
- 🔄 Planned - On development roadmap
- ❌ Deprecated - Will be removed
Error Handling - Zero Tolerance
All errors must be handled with detailed logging - no empty catch blocks allowed.
Quick Implementation Guide
1. Repository Setup
mkdir my-mcp-server
cd my-mcp-server
2. FastMCP Configuration
from fastmcp import FastMCP
app = FastMCP("server-name", version="1.0.0")
@app.tool()
async def sample_workflow(iterations: int = 5):
pass
3. Error Handling
try:
result = await risky_operation()
except SpecificError as e:
logger.error(f"Detailed error: {e}", extra={
"correlation_id": request_id,
"operation": "risky_operation"
})
4. Testing Requirements
- Unit tests: 80% minimum coverage
- Integration tests: 70% minimum coverage
- End-to-end tests for critical workflows
Progressive Usage
Level 1: Basic Setup
Start with MCP Scaffolding for project structure.
Level 2: Core Development
Implement AI Sampling for creative workflows.
Level 3: Quality Assurance
Apply Testing Standards and Error Handling.
Level 4: Production Ready
Implement Monitoring and Docker Standards.
Common Patterns
Repository Structure
mcp-server/
├── src/mcp_server_name/
├── tests/
├── docs/
├── pyproject.toml
├── README.md
└── .mcp-standards.yaml
Tool Implementation
@app.tool()
async def example_tool(ctx, param: str) -> dict:
"""Tool with proper error handling and logging."""
try:
result = await process_data(param)
logger.info("Tool executed successfully", extra={
"tool": "example_tool",
"param_length": len(param)
})
return {"success": True, "result": result}
except Exception as e:
logger.error(f"Tool execution failed: {e}", extra={
"tool": "example_tool",
"error_type": type(e).__name__,
"correlation_id": ctx.get("correlation_id")
})
return {"error": str(e)}
Standards Compliance Checklist
Getting Help
Standards Reference
Troubleshooting
This skill provides hierarchical access to thousands of lines of MCP standards documentation, loading only the relevant sections for your current development task.
