mcp-builder

Overview of mcp-builder skill

What mcp-builder helps you build

mcp-builder is a practical guide skill for MCP Server Development: designing, implementing, and evaluating Model Context Protocol servers that let LLMs use external APIs through well-structured tools. It is best for developers who already know the service they want to integrate and need help turning API capabilities into agent-friendly MCP tools rather than thin endpoint wrappers.

Best-fit users and projects

Use the mcp-builder skill when you are building a new MCP server in Python with FastMCP or in Node/TypeScript with the official MCP SDK. It is especially useful for API integrations where tool design matters: naming, input schemas, pagination, error handling, OAuth/security, response shaping, and evaluation questions. It is less useful if you only need a quick local script, a one-off API wrapper, or a non-MCP integration.

Main differentiator: agent-centric tool design

The strongest value of mcp-builder is its emphasis on workflows, not just API coverage. It pushes you to create tools that help an LLM complete real tasks with limited context: concise outputs, stable schemas, clear descriptions, safe operations, and predictable errors. That makes it more decision-oriented than a generic “write an MCP server” prompt.

Repository materials worth knowing

The skill includes SKILL.md, implementation references for Python and Node/TypeScript, an MCP best-practices guide, and an evaluation harness. Read these first:

• SKILL.md for the overall workflow
• reference/mcp_best_practices.md for naming, pagination, truncation, security, and error standards
• reference/python_mcp_server.md for FastMCP patterns
• reference/node_mcp_server.md for TypeScript SDK patterns
• reference/evaluation.md and scripts/evaluation.py for testing whether agents can actually use your tools

How to Use mcp-builder skill

mcp-builder install and first read

Install the skill from the GitHub skill repository:

npx skills add ComposioHQ/awesome-claude-skills --skill mcp-builder

After installation, open SKILL.md first, then jump to the language-specific reference that matches your stack. If you are still deciding between Python and Node, compare the quick references: FastMCP gives a compact decorator-based path with Pydantic validation, while Node/TypeScript uses McpServer, registerTool, and Zod schemas.

Inputs the skill needs from you

mcp-builder usage improves sharply when you provide more than “build an MCP server for X.” Give the agent:

• Target service/API and authentication method
• Primary user workflows, not just endpoint names
• Preferred language: Python/FastMCP or Node/TypeScript
• Read-only vs write-capable tool boundaries
• Expected tool count and naming style
• Pagination, rate-limit, and response-size constraints
• Example real tasks the LLM should complete
• Any existing OpenAPI docs, SDK docs, or API examples

A weak prompt is: “Create a GitHub MCP server.”
A stronger prompt is: “Use mcp-builder to design a Python FastMCP server for GitHub issue triage. Prioritize read-only tools for listing repositories, searching issues, fetching issue details, and summarizing labels/comments. Follow {service}_{action}_{resource} tool naming, include pagination with limit and next_offset, and keep responses under a 25,000 character limit.”

Suggested workflow for real projects

Start with planning before code. Ask the skill to identify the top workflows an agent should complete, then map those workflows to a small tool set. Next, generate schemas and descriptions, then implementation, then evaluation questions.

A practical mcp-builder guide workflow:

1. Define 5-10 real tasks the MCP server should enable.
2. Consolidate API calls into workflow-level tools where appropriate.
3. Choose Python or Node/TypeScript and follow the matching reference file.
4. Add validation, pagination, truncation, and actionable errors early.
5. Create read-only evaluation questions before expanding write operations.
6. Run or adapt scripts/evaluation.py to test whether a model can solve tasks with only your tools.

Practical prompt pattern

Use prompts that force design decisions before implementation:

Use mcp-builder for MCP Server Development. Review the target API capabilities below, propose an agent-friendly tool list, explain which API endpoints each tool uses internally, then generate a FastMCP implementation. Each tool must include clear docstrings, Pydantic validation, pagination where needed, concise JSON/Markdown responses, and stable error messages. Also create 10 read-only evaluation questions with single verifiable answers.

This pattern works because it asks for workflow design, implementation, and evaluation instead of treating the MCP server as a direct API mirror.

mcp-builder skill FAQ

Is mcp-builder only for experienced MCP developers?

No, but it is not a pure beginner tutorial. A beginner can use it effectively if they understand basic API requests, authentication, and either Python or TypeScript. The included reference files reduce guesswork by showing concrete SDK patterns, naming rules, schema validation, and evaluation expectations.

How is mcp-builder different from an ordinary prompt?

An ordinary prompt may generate working code but often misses MCP-specific quality issues: unclear tool names, overly broad outputs, missing pagination, weak docstrings, unsafe write actions, or schemas that confuse agents. mcp-builder encodes MCP conventions and evaluation thinking so the output is more likely to be usable by LLM clients, not just syntactically valid.

When should I not use mcp-builder?

Do not use mcp-builder if you are not building an MCP server, if your integration does not need LLM tool access, or if you only want a direct SDK wrapper with one tool per API endpoint. It may also be overkill for prototypes where evaluation, security boundaries, and response design do not matter yet.

Does it support both Python and TypeScript?

Yes. The repository includes separate guidance for Python FastMCP and Node/TypeScript MCP SDK implementations. For Python, review reference/python_mcp_server.md; for TypeScript, review reference/node_mcp_server.md. Both paths emphasize validation, naming, error handling, and tool registration, but the implementation idioms differ.

How to Improve mcp-builder skill

Improve mcp-builder results with workflow examples

The most common failure mode is asking for tools based only on API endpoints. Improve results by supplying realistic user tasks: “find overdue invoices and draft reminder notes” is better than “wrap invoice endpoints.” mcp-builder can then design tools around agent outcomes, combine related API calls, and avoid exposing low-value primitives.

Tighten schemas, names, and descriptions

After the first output, inspect every tool as if the LLM has no extra context. Tool names should be predictable, usually service-prefixed snake_case such as github_search_issues. Parameters should make required and optional fields obvious. Descriptions should say when to use the tool, what it returns, and important limits. If a parameter is ambiguous, ask the skill to revise the schema and examples before coding further.

Use evaluation to find weak tools

The included evaluation guidance is a major reason to install this skill. Create 10 read-only, independent, non-destructive questions with single stable answers. If the agent needs many calls, gets confused, or receives huge responses, that is useful feedback. Use those failures to refine pagination, filtering, result summaries, and tool descriptions.

Iterate after the first generated server

Do not treat the first generated MCP server as final. Ask mcp-builder to review the implementation against reference/mcp_best_practices.md, then request a focused improvement pass for security, truncation, errors, and evaluation readiness. Strong follow-up prompt: “Audit this MCP server for agent usability. Identify tools that return too much data, parameters that are unclear, missing pagination, unsafe write operations, and evaluation questions that would expose these problems.”