mcp-developer Checked

Use when building, debugging, or extending MCP servers or clients that connect AI systems with external tools and data sources. Invoke to implement tool handlers, configure resource providers, set up stdio/HTTP/SSE transport layers, validate schemas with Zod or Pydantic, debug protocol compliance issues, or scaffold complete MCP server/client projects using TypeScript or Python SDKs.

MCP Developer

Senior MCP (Model Context Protocol) developer with deep expertise in building servers and clients that connect AI systems with external tools and data sources.

Use when building, debugging, or extending MCP servers or clients that connect AI systems with external tools and data sources. Invoke to implement tool handlers, configure resource providers, set up stdio/HTTP/SSE transport layers, validate schemas with Zod or Pydantic, debug protocol compliance issues, or scaffold complete MCP server/client projects using TypeScript or Python SDKs.

MCP Developer

Senior MCP (Model Context Protocol) developer with deep expertise in building servers and clients that connect AI systems with external tools and data sources.

Core Workflow

1. **Analyze requirements** — Identify data sources, tools needed, and client apps

2. **Initialize project** — npx @modelcontextprotocol/create-server my-server (TypeScript) or pip install mcp + scaffold (Python)

3. **Design protocol** — Define resource URIs, tool schemas (Zod/Pydantic), and prompt templates

4. **Implement** — Register tools and resource handlers; configure transport (stdio/SSE/HTTP)

5. **Test** — Run npx @modelcontextprotocol/inspector to verify protocol compliance interactively; confirm tools appear, schemas accept valid inputs, and error responses are well-formed JSON-RPC 2.0. **Feedback loop:** if schema validation fails → inspect Zod/Pydantic error output → fix schema definition → re-run inspector. If a tool call returns a malformed response → check transport serialisation → fix handler → re-test.

6. **Deploy** — Package, add auth/rate-limiting, configure env vars, monitor

Reference Guide

Load detailed guidance based on context:

| Topic | Reference | Load When |

|-------|-----------|-----------|

| Protocol | references/protocol.md | Message types, lifecycle, JSON-RPC 2.0 |

| TypeScript SDK | references/typescript-sdk.md | Building servers/clients in Node.js |

| Python SDK | references/python-sdk.md | Building servers/clients in Python |

| Tools | references/tools.md | Tool definitions, schemas, execution |

| Resources | references/resources.md | Resource providers, URIs, templates |

Minimal Working Example

### TypeScript — Tool with Zod Validation

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

const server = new McpServer({ name: "my-server", version: "1.1.0" });

// Register a tool with validated input schema
server.tool(
  "get_weather",
  "Fetch current weather for a location",
  {
    location: z.string().min(1).describe("City name or coordinates"),
    units: z.enum(["celsius", "fahrenheit"]).default("celsius"),
  },
  async ({ location, units }) => {
    // Implementation: call external API, transform response
    const data = await fetchWeather(location, units); // your fetch logic
    return {
      content: [{ type: "text", text: JSON.stringify(data) }],
    };
  }
);