MCP Server Creator

Overview

This skill automates the creation of Model Context Protocol (MCP) servers—the standardized way to connect AI applications to external data sources, tools, and workflows.

Key Capabilities:

• Interactive requirements gathering and language selection
• Project scaffolding with SDK integration (TypeScript/Python)
• Server implementation with tools, resources, and prompts
• Claude Desktop configuration generation
• Testing workflow with MCP Inspector

When to Use This Skill

Trigger Phrases:

• "create an MCP server for [purpose]"
• "build a Model Context Protocol server"
• "set up MCP integration with [data source]"
• "generate MCP server to expose [tools/data]"

Use Cases:

• Exposing custom data sources to AI applications
• Creating tools for AI models to call
• Building enterprise integrations for Claude

NOT for:

• Consuming existing MCP servers (this creates new ones)
• Non-AI integrations (use REST APIs instead)
• Simple file operations (use built-in tools)

Response Style

• Interactive: Ask clarifying questions about purpose and capabilities
• Educational: Explain MCP concepts and best practices
• Language-aware: Support TypeScript and Python SDKs
• Production-ready: Generate complete, tested configurations

Quick Decision Matrix

User Request	Action	Reference
"create MCP server"	Full workflow	Start at Phase 1
"TypeScript MCP setup"	Skip to Phase 2	workflow/phase-2-structure.md
"add tools to MCP server"	Implementation	workflow/phase-3-implementation.md
"configure Claude Desktop"	Integration	workflow/phase-5-integration.md
"test MCP server"	Validation	workflow/phase-6-testing.md

Workflow Overview

Phase 1: Discovery & Language Selection

Understand server purpose, target AI app, and choose SDK. → Details: workflow/phase-1-discovery.md

Phase 2: Project Structure Generation

Create project with dependencies and configuration. → Details: workflow/phase-2-structure.md

Phase 3: Server Implementation

Generate core server code with tools/resources/prompts. → Details: workflow/phase-3-implementation.md

Phase 4: Environment & Security

Configure secrets and security best practices. → Details: workflow/phase-4-security.md

Phase 5: Claude Desktop Integration

Generate configuration for immediate use. → Details: workflow/phase-5-integration.md

Phase 6: Testing & Validation

Verify with MCP Inspector and Claude Desktop. → Details: workflow/phase-6-testing.md

Phase 7: Documentation & Handoff

Provide README and next steps. → Details: workflow/phase-7-documentation.md

Important Reminders

1. STDIO = No stdout logging - Use console.error or stderr only
2. Build before test - TypeScript requires npm run build
3. Absolute paths only - Claude Desktop config needs full paths
4. Complete restart required - Quit Claude Desktop entirely (Cmd+Q)
5. Schemas matter - AI uses descriptions to decide when to call tools
6. Security first - Never commit secrets, validate all inputs
7. Test incrementally - MCP Inspector before Claude integration

Limitations

• Only TypeScript and Python SDKs fully supported
• HTTP transport requires additional security setup
• Claude Desktop must be restarted for config changes
• Cannot modify existing MCP servers (creates new ones only)

Reference Materials

Resource	Purpose
workflow/*.md	Detailed phase instructions
reference/capabilities.md	Tools, resources, prompts deep-dive
reference/troubleshooting.md	Common issues and debugging
reference/language-guides/*.md	TypeScript and Python best practices

Success Criteria

• Project structure created with dependencies
• Server implements requested capabilities
• All tools have proper schemas and descriptions
• Logging configured correctly (no stdout for STDIO)
• Environment variables configured securely
• Claude Desktop config generated with absolute paths
• MCP Inspector testing passes
• Server appears in Claude Desktop after restart