Mcp Builder

🏢Official
by anthropics · vlatest · Repository

Official anthropics skill for MCP tools — helps with orchestrating AI agents and multi-step workflows.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

1

Run in terminal (recommended)

terminal
claude mcp add mcp-builder npx -- -y @trustedskills/mcp-builder
2

Or manually add to ~/.claude/settings.json

~/.claude/settings.json
{
  "mcpServers": {
    "mcp-builder": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/mcp-builder"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

What it does

The Mcp Builder skill provides a comprehensive guide for developing high-quality MCP (Model Context Protocol) servers. These servers enable Large Language Models (LLMs) to interact with external services through well-defined tools, ultimately allowing agents to accomplish real-world tasks. The skill focuses on best practices across four phases: research, implementation, testing, and evaluation, with specific guidance for TypeScript and Python development. It emphasizes API coverage and clear tool naming over complex workflow tools.

When to use it

  • When building an MCP server to connect LLMs to external services.
  • If you want to ensure your MCP server enables effective agent performance on real-world tasks.
  • For developers using TypeScript or Python to implement MCP servers and seeking best practices.
  • When needing a structured evaluation framework for validating the effectiveness of your MCP server with an LLM.

Key capabilities

  • Four-phase workflow (research, implementation, testing, evaluation) for building MCP servers.
  • Guidance on balancing API coverage versus specialized workflow tools.
  • Best practices for clear and consistent tool naming conventions using prefixes.
  • Recommendations for input/output schemas, pagination, response formatting, and tool annotations (readOnly, destructive, idempotent, openWorld hints).
  • An evaluation framework requiring 10 complex questions with verifiable XML answers to validate LLM effectiveness.

Example prompts

  • "Guide me through the research phase of building an MCP server."
  • "What are best practices for naming tools in my MCP server?"
  • "Show me code examples for implementing pagination in a TypeScript MCP tool."

Tips & gotchas

  • Prioritize comprehensive API coverage over workflow tools when unsure, as performance varies by client.
  • The evaluation framework requires creating 10 independent, read-only questions with verifiable answers in XML format to properly assess your server's effectiveness.
  • Consistent tool naming and clear descriptions are crucial for agent discoverability and efficient operation.

Tags

🛡️

TrustedSkills Verification

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Details

Version
vlatest
License
Author
anthropics
Installs
16.5k

🏢 Official

Published by the company or team that built the technology.