| name | mcp-server-builder |
| description | Use when creating MCP (Model Context Protocol) servers for any API or service. Auto-generate tools, resources, and prompts that any AI agent can use. |
| domain | mcp |
| author | oyi77 |
| license | Apache-2.0 |
| subdomain | mcp |
| tags | ["ai-agent","api","builder","mcp","mcp-server","model-context-protocol","server","tool-integration"] |
| persona | {"name":"Anthropic MCP Team","expertise":"Protocol design, API integration, AI agent architecture","philosophy":"Standards enable interoperability","credentials":"Created MCP standard at Anthropic"} |
| version | 1.0.0 |
Mcp Server Builder
When to Use
Trigger phrases:
- "mcp server builder"
- "Help me with mcp server builder"
Use cases:
- When the task matches this skill's domain expertise
When NOT to use:
- For tasks outside this skill's scope
mcp generate --spec https://api.example.com/openapi.json
Or create custom server
mcp create --name "my-service" --tools getData,postData
### What is MCP?
MCP is a protocol that allows AI systems to access external tools and data through a standardized interface. Think USB-C for AI applications.
### Server Components
**Tools:** Functions the AI can call
```json
{
"name": "searchDatabase",
"description": "Search company database",
"input_schema": {
"query": "string",
"limit": "number"
}
}
Resources: Data the AI can read
{
"uri": "docs://readme",
"name": "Project README",
"mimeType": "text/markdown"
}
Prompts: Pre-defined templates
{
"name": "debug_error",
"template": "Analyze this error: {{error}}"
}
Building a Server
- Define your API endpoints as tools
- Document responses as resources
- Create reusable prompts
- Package and distribute
Integration
Works with Claude Code, Cursor, and any MCP-compatible client.
When NOT to Use
- When a simpler HTTP client would suffice