Back to Skills

scaffold-mcp-server

pjt222
Updated Yesterday
2 views
17
2
17
View on GitHub
Testingaitestingmcp

About

This skill scaffolds a complete, runnable MCP server project from a tool specification using the official TypeScript or Python SDK. It generates the proper project structure, transport configuration, tool handlers, and a test harness. Use it when you have a spec and need a working server, are starting a new MCP project, migrating an existing integration, or prototyping a tool surface.

Quick Install

Claude Code

Recommended
Primary
npx skills add pjt222/agent-almanac -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternative
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/scaffold-mcp-server

Copy and paste this command in Claude Code to install this skill

Documentation

Scaffold MCP Server

Generate runnable MCP server project from tool spec → official MCP SDK (TS|Py).

Use When

  • Have spec (from analyze-codebase-for-mcp or manual) + need server
  • New MCP project → right structure from start
  • Migrate existing tool integ → MCP protocol
  • Prototype tool surface → test w/ Claude Code pre-full-impl
  • Need scaffold + test harness for CI

In

  • Required: Tool spec doc (YAML|JSON: tool names, params, return types)
  • Required: Lang (typescript|python)
  • Required: Transport (stdio|sse)
  • Optional: Output dir (default: cwd)
  • Optional: Pkg name + ver
  • Optional: Auth (none|bearer-token|api-key)
  • Optional: Docker (true|false, default false)

Do

Step 1: SDK Lang + Transport

1.1. Lang by ctx:

  • TS: Node.js, web-adj, JSON-heavy
  • Py: Data sci, ML, scientific tools

1.2. Transport:

  • stdio: Default local. Claude Code launches as subprocess.
  • SSE: Remote|shared. Needs HTTP host.

1.3. Auth:

  • none: Local stdio (proc-level trust)
  • bearer-token: Remote SSE w/ static tokens
  • api-key: Remote w/ per-client keys

→ Lang, transport, auth documented.

If err: ambiguous → default TS + stdio + no auth → fastest time-to-working.

Step 2: Init Project

2.1. Mkdir + init:

TS:

mkdir -p $PROJECT_NAME && cd $PROJECT_NAME
npm init -y
npm install @modelcontextprotocol/sdk zod
npm install -D typescript @types/node tsx
npx tsc --init --target ES2022 --module nodenext --moduleResolution nodenext --outDir dist

Py:

mkdir -p $PROJECT_NAME && cd $PROJECT_NAME
python -m venv .venv
source .venv/bin/activate
pip install mcp pydantic

2.2. Standard structure:

$PROJECT_NAME/
├── src/
│   ├── index.ts|main.py      # Server entry point
│   ├── tools/                 # One file per tool category
│   │   ├── index.ts|__init__.py
│   │   └── [category].ts|.py
│   └── utils/                 # Shared utilities
│       └── validation.ts|.py
├── test/
│   ├── harness.ts|.py         # MCP test harness
│   └── tools/
│       └── [category].test.ts|.py
├── package.json|pyproject.toml
├── tsconfig.json              # TypeScript only
├── Dockerfile                 # If Docker requested
└── README.md

2.3. Bin entry npm (TS) | entry point Py:

TS package.json:

{
  "name": "$PACKAGE_NAME",
  "version": "1.0.0",
  "type": "module",
  "bin": { "$PACKAGE_NAME": "./dist/index.js" },
  "scripts": {
    "build": "tsc",
    "start": "node dist/index.js",
    "dev": "tsx src/index.ts",
    "test": "tsx test/harness.ts"
  }
}

→ Buildable skeleton w/ all deps installed.

If err: install fails → check net + registry. TS → Node ≥18. Py → Py ≥3.10.

Step 3: Tool Handlers from Spec

3.1. Parse spec → per tool, gen handler:

TS template:

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

export function registerTools(server: McpServer): void {
  server.tool(
    "tool_name",
    "Tool description from spec",
    {
      param1: z.string().describe("Parameter description"),
      param2: z.number().optional().default(10).describe("Optional param"),
    },
    async ({ param1, param2 }) => {
      try {
        // TODO: Implement tool logic
        const result = await performAction(param1, param2);
        return {
          content: [{ type: "text", text: JSON.stringify(result, null, 2) }],
        };
      } catch (error) {
        return {
          content: [{ type: "text", text: `Error: ${(error as Error).message}` }],
          isError: true,
        };
      }
    }
  );
}

Py template:

from mcp.server import Server
from mcp.types import Tool, TextContent
from pydantic import BaseModel

class ToolNameParams(BaseModel):
    param1: str
    param2: int = 10

async def handle_tool_name(params: ToolNameParams) -> list[TextContent]:
    try:
        result = await perform_action(params.param1, params.param2)
        return [TextContent(type="text", text=json.dumps(result, indent=2))]
    except Exception as e:
        return [TextContent(type="text", text=f"Error: {e}")]

3.2. One handler file per category from spec.

3.3. Validation beyond type checking:

  • String len limits
  • Numeric bounds
  • Enum constraints
  • Required field enforce

3.4. Structured err responses for anticipated failures.

→ Handler file per category w/ typed params + err handling.

If err: ambiguous types → default string + TODO for manual refine.

Step 4: Configure Transport

4.1. Server entry w/ chosen transport:

stdio (TS):

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { registerTools } from "./tools/index.js";

const server = new McpServer({
  name: "$PACKAGE_NAME",
  version: "1.0.0",
});

registerTools(server);

const transport = new StdioServerTransport();
await server.connect(transport);

SSE (TS):

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { SSEServerTransport } from "@modelcontextprotocol/sdk/server/sse.js";
import { registerTools } from "./tools/index.js";

const server = new McpServer({
  name: "$PACKAGE_NAME",
  version: "1.0.0",
});

registerTools(server);

const transport = new SSEServerTransport("/messages", response);
await server.connect(transport);

4.2. Auth req → middleware:

  • Bearer token → validate Authorization header
  • API key → validate X-API-Key header

4.3. Shebang for stdio → direct exec:

#!/usr/bin/env node

→ Working entry starts MCP server on transport.

If err: SDK ver ≠ import paths → check @modelcontextprotocol/sdk ver + adjust. SDK restructured paths between vers.

Step 5: Test Harness

5.1. Validate every tool:

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { InMemoryTransport } from "@modelcontextprotocol/sdk/inMemory.js";
import { Client } from "@modelcontextprotocol/sdk/client/index.js";

async function runTests(): Promise<void> {
  const server = createServer();
  const [clientTransport, serverTransport] = InMemoryTransport.createLinkedPair();

  await server.connect(serverTransport);
  const client = new Client({ name: "test-client", version: "1.0.0" });
  await client.connect(clientTransport);

  // Test: tools/list returns all expected tools
  const tools = await client.listTools();
  console.assert(tools.tools.length === EXPECTED_TOOL_COUNT);

  // Test: each tool with valid input
  for (const tool of tools.tools) {
    const result = await client.callTool({
      name: tool.name,
      arguments: getTestInput(tool.name),
    });
    console.assert(!result.isError, `${tool.name} failed`);
  }

  // Test: each tool with invalid input returns isError
  for (const tool of tools.tools) {
    const result = await client.callTool({
      name: tool.name,
      arguments: getInvalidInput(tool.name),
    });
    console.assert(result.isError, `${tool.name} should reject invalid input`);
  }

  console.log("All tests passed");
}

5.2. Test fixtures per tool: valid, invalid, edge cases.

5.3. Add test script → package.json | pyproject.toml.

→ Harness exercises every tool w/ valid+invalid.

If err: InMemoryTransport not in SDK ver → fall back to spawning server as subproc + stdio pipes.

Step 6: Docs + Config

6.1. Gen README.md w/:

  • Project desc
  • Install instructions
  • Claude Code config cmd
  • Claude Desktop JSON snippet
  • Tool listing w/ descs + param schemas
  • Dev + test instructions

6.2. Gen Claude Code register cmd:

# stdio transport
claude mcp add $PACKAGE_NAME stdio "node" "dist/index.js"

# SSE transport
claude mcp add $PACKAGE_NAME -e API_KEY=your_key -- mcp-remote http://localhost:3000/mcp

6.3. Gen Claude Desktop config:

{
  "mcpServers": {
    "$PACKAGE_NAME": {
      "command": "node",
      "args": ["path/to/dist/index.js"]
    }
  }
}

6.4. Docker requested → gen Dockerfile:

FROM node:20-slim AS build
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

FROM node:20-slim
WORKDIR /app
COPY --from=build /app/dist ./dist
COPY --from=build /app/node_modules ./node_modules
COPY --from=build /app/package.json .
ENTRYPOINT ["node", "dist/index.js"]

→ Complete docs + config for immediate use.

If err: README has placeholders → search project for actual vals to substitute. Docker fail → verify base img matches Node|Py ver.

Check

  • Builds w/o errs (npm run build|equiv)
  • Server starts + responds tools/list JSON-RPC
  • Every tool from spec registered + discoverable
  • Harness passes valid inputs all tools
  • Harness confirms err responses invalid inputs
  • Claude Code connects via claude mcp add
  • README has working install + config
  • Gen code passes lint (if configured)

Traps

  • SDK import path changes: @modelcontextprotocol/sdk restructured between vers. Check installed ver export paths.
  • Forget shebang: stdio invoked directly needs #!/usr/bin/env node first line.
  • Block event loop: TS handlers must async. Sync ops block all other tool calls.
  • Missing type: "module": SDK uses ESM. Without → Node treats as CJS, imports fail.
  • Zod schema drift: Spec evolves but Zod not updated → silent fails. Gen schemas from single source of truth.
  • stdout pollution: stdio uses stdout for JSON-RPC. Any console.log in handlers corrupts. Use console.error|file logger.

  • analyze-codebase-for-mcp — gen spec this skill consumes
  • build-custom-mcp-server — manual impl for complex
  • configure-mcp-server — connect scaffold → Claude Code/Desktop
  • troubleshoot-mcp-connection — debug post-deploy
  • containerize-mcp-server — Docker for distribution

GitHub Repository

pjt222/agent-almanac
Path: i18n/caveman-ultra/skills/scaffold-mcp-server
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

Related Skills

evaluating-llms-harness

Testing

This Claude Skill runs the lm-evaluation-harness to benchmark LLMs across 60+ standardized academic tasks like MMLU and GSM8K. It's designed for developers to compare model quality, track training progress, or report academic results. The tool supports various backends including HuggingFace and vLLM models.

View skill

cloudflare-cron-triggers

Testing

This skill provides comprehensive knowledge for implementing Cloudflare Cron Triggers to schedule Workers using cron expressions. It covers setting up periodic tasks, maintenance jobs, and automated workflows while handling common issues like invalid cron expressions and timezone problems. Developers can use it for configuring scheduled handlers, testing cron triggers, and integrating with Workflows and Green Compute.

View skill

webapp-testing

Testing

This Claude Skill provides a Playwright-based toolkit for testing local web applications through Python scripts. It enables frontend verification, UI debugging, screenshot capture, and log viewing while managing server lifecycles. Use it for browser automation tasks but run scripts directly rather than reading their source code to avoid context pollution.

View skill

finishing-a-development-branch

Testing

This skill helps developers complete finished work by verifying tests pass and then presenting structured integration options. It guides the workflow for merging, creating PRs, or cleaning up branches after implementation is done. Use it when your code is ready and tested to systematically finalize the development process.

View skill