mcp-developer
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.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/jeffallan/claude-skills --skill mcp-developer- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads mcp-developer automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
- Analyze requirements — Identify data sources, tools needed, and client apps
- Initialize project —
npx @modelcontextprotocol/create-server my-server(TypeScript) orpip install mcp+ scaffold (Python) - Design protocol — Define resource URIs, tool schemas (Zod/Pydantic), and prompt templates
- Implement — Register tools and resource handlers; configure transport (stdio/SSE/HTTP)
- Test — Run
npx @modelcontextprotocol/inspectorto 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. - 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) }],
};
}
);
// Register a resource provider
server.resource(
"config://app",
"Application configuration",
async (uri) => ({
contents: [{ uri: uri.href, text: JSON.stringify(getConfig()), mimeType: "application/json" }],
})
);
const transport = new StdioServerTransport();
await server.connect(transport);
Python — Tool with Pydantic Validation
from mcp.server.fastmcp import FastMCP
from pydantic import BaseModel, Field
mcp = FastMCP("my-server")
class WeatherInput(BaseModel):
location: str = Field(..., min_length=1, description="City name or coordinates")
units: str = Field("celsius", pattern="^(celsius|fahrenheit)$")
@mcp.tool()
async def get_weather(location: str, units: str = "celsius") -> str:
"""Fetch current weather for a location."""
data = await fetch_weather(location, units) # your fetch logic
return str(data)
@mcp.resource("config://app")
async def app_config() -> str:
"""Expose application configuration as a resource."""
return json.dumps(get_config())
if __name__ == "__main__":
mcp.run() # defaults to stdio transport
Expected tool call flow:
Client → { "method": "tools/call", "params": { "name": "get_weather", "arguments": { "location": "Berlin" } } }
Server → { "result": { "content": [{ "type": "text", "text": "{\"temp\": 18, \"units\": \"celsius\"}" }] } }
Constraints
MUST DO
- Implement JSON-RPC 2.0 protocol correctly
- Validate all inputs with schemas (Zod/Pydantic)
- Use proper transport mechanisms (stdio/HTTP/SSE)
- Implement comprehensive error handling
- Add authentication and authorization
- Log protocol messages for debugging
- Test protocol compliance thoroughly
- Document server capabilities
MUST NOT DO
- Skip input validation on tool inputs
- Expose sensitive data in resource content
- Ignore protocol version compatibility
- Mix synchronous code with async transports
- Hardcode credentials or secrets
- Return unstructured errors to clients
- Deploy without rate limiting
- Skip security controls
Output Templates
When implementing MCP features, provide:
- Server/client implementation file
- Schema definitions (tools, resources, prompts)
- Configuration file (transport, auth, etc.)
- Brief explanation of design decisions
Maintained by @jeffallan, Principal Consultant at Synergetic Solutions
FAQ
What does the mcp-developer skill do?
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.
How do I install mcp-developer?
Run npx skills add https://github.com/jeffallan/claude-skills --skill mcp-developer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/mcp-developer/ (personal) or .claude/skills/mcp-developer/ (project).
Which AI agents can use mcp-developer?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is mcp-developer safe to install?
Security partners have reviewed it: Gen Agent Trust Hub flagged risks; Socket flagged items to review; Snyk passed; Runlayer passed; ZeroLeaks passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains mcp-developer?
It is published by jeffallan in jeffallan/claude-skills. It has 4,217 recorded installs.
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