Skip to content
TrustedSkillsbeta
Back to all skills

Mcp Builder

Listed
eddiebe147·vlatest·agents

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Repository

Install on your platform

This skill no longer installs under the name mcp-builder. eddiebe147/claude-settings is deleted or private, so it cannot be installed from.

We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-22. We don't show a command we know will fail.

Repository install instructions

What we know about this skill

Publisher

eddiebe147

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. repository not found or private Source recorded as eddiebe147/claude-settings.
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill provides guidance and assistance for developing high-quality MCP (Model Context Protocol) servers. An MCP server enables Large Language Models (LLMs) to interact with external services and APIs, allowing them to accomplish real-world tasks through orchestrated workflows. The focus is on building tools that are specifically designed for AI agents, rather than simply wrapping existing API endpoints. This skill guides users through the process of creating these servers, emphasizing thoughtful design and iterative development based on agent performance.

When to use it

  • When you need to create tools that allow an LLM to access external services or APIs.
  • If you are designing a workflow for an AI agent that requires interaction with multiple systems.
  • To ensure your MCP server adheres to best practices and facilitates effective LLM task completion.

Key capabilities

  • Agent-Centric Design Principles: Guidance on building tools optimized for AI agents, including considerations for workflows, limited context windows, actionable error messages, and natural task subdivisions.
  • MCP Protocol Documentation Access: Instructions on retrieving the latest MCP protocol specification using WebFetch.
  • Framework Documentation Access: Provides links to and instructions for loading relevant documentation for Python and Node/TypeScript implementations, including SDK best practices and implementation guides.
  • Evaluation-Driven Development: Encourages creating realistic evaluation scenarios and iterating based on agent feedback.

Example prompts

  • "What are the key principles for designing tools for AI agents using MCP?"
  • "How do I retrieve the latest Model Context Protocol documentation?"
  • "Where can I find best practices for implementing an MCP server in Python?"

Tips & gotchas

  • This skill focuses on development guidance, not providing a ready-made MCP server. You will need to implement the server yourself, using the provided resources.
  • Pay close attention to the "Optimize for Limited Context" principles – agents have constrained context windows and efficient tool design is crucial.
  • The skill relies on WebFetch to load external documentation; ensure this tool is available within your agent environment.