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Mcp server builder

Skill sinhoneyy/master-skills/plugins/master-skills-ai-agent-builder/skills/mcp-server-builder

Unified skill library for Claude, Codex, Cursor, Antigravity & AI agents — 2,658 skills across 15 domains

Install
npx -y skills add sinhoneyy/master-skills --skill mcp-server-builder

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What its author says it does

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Design and ship production-ready MCP (Model Context Protocol) servers from OpenAPI contracts instead of hand-written tool wrappers. Python and TypeScript support, schema validation, safe evolution. Use when exposing an existing API as an MCP server, building tool integrations for Claude or Codex or Cursor, or scaffolding an MCP project from scratch.

SKILL.md

3.9 KB, 744 tokens by cl100k_base, as published. Nobody here has run it

MCP Server Builder

Tier: POWERFUL · Category: Engineering · Domain: AI / API Integration

Overview

Use this skill to design and ship production-ready MCP servers from API contracts instead of hand-written one-off tool wrappers. It focuses on fast scaffolding, schema quality, validation, and safe evolution.

The workflow supports both Python and TypeScript MCP implementations and treats OpenAPI as the source of truth.

Core Capabilities

  • Convert OpenAPI paths/operations into MCP tool definitions
  • Generate starter server scaffolds (Python or TypeScript)
  • Enforce naming, descriptions, and schema consistency
  • Validate MCP tool manifests for common production failures
  • Apply versioning and backward-compatibility checks
  • Separate transport/runtime decisions from tool contract design

When to Use

  • You need to expose an internal/external REST API to an LLM agent
  • You are replacing brittle browser automation with typed tools
  • You want one MCP server shared across teams and assistants
  • You need repeatable quality checks before publishing MCP tools
  • You want to bootstrap an MCP server from existing OpenAPI specs

Key Workflows

1. OpenAPI to MCP Scaffold

  1. Start from a valid OpenAPI spec.
  2. Generate tool manifest + starter server code.
  3. Review naming and auth strategy.
  4. Add endpoint-specific runtime logic.
python3 scripts/openapi_to_mcp.py \
  --input openapi.json \
  --server-name billing-mcp \
  --language python \
  --output-dir ./out \
  --format text

Supports stdin as well:

cat openapi.json | python3 scripts/openapi_to_mcp.py --server-name billing-mcp --language typescript

2. Validate MCP Tool Definitions

Run validator before integration tests:

python3 scripts/mcp_validator.py --input out/tool_manifest.json --strict --format text

Checks include duplicate names, invalid schema shape, missing descriptions, empty required fields, and naming hygiene.

3. Runtime Selection

  • Choose Python for fast iteration and data-heavy backends.
  • Choose TypeScript for unified JS stacks and tighter frontend/backend contract reuse.
  • Keep tool contracts stable even if transport/runtime changes.

4. Harden for Production

Key items before publishing:

  • Keep secrets in env vars, not tool schemas
  • Prefer outbound host allowlists over open proxies
  • Use additive-only changes; never rename tool names in-place

Full hardening guidance: references/production-hardening-guide.md.

Script Interfaces

  • python3 scripts/openapi_to_mcp.py --help
    • Reads OpenAPI from stdin or --input
    • Produces manifest + server scaffold
    • Emits JSON summary or text report
  • python3 scripts/mcp_validator.py --help
    • Validates manifests and optional runtime config
    • Returns non-zero exit in strict mode when errors exist

Reference Material

What ships with it: 8 files

22.0 KB alongside SKILL.md, 2 of them executable

references/

scripts/

Gives 0 of the 12 instructions most mcp tooling skills give in 744 tokens

Counted across 638 of the 750 authors here whose files we hold, read 2026-08-07

  • create ten complex read-only evaluation questionsin 69 of 638, across 15 files
  • test servers using MCP Inspectorin 61 of 638, across 19 files
  • provide actionable error messagesin 54 of 638, across 12 files
  • prioritize comprehensive API coverage over specific workflowsin 54 of 638, across 12 files
  • use TypeScript and Streamable HTTP for remote serversin 54 of 638, across 8 files
  • define structured output schemas where possiblein 50 of 638, across 8 files
  • use Zod or Pydantic for input schemasin 47 of 638, across 5 files
  • fetch MCP specification pages with markdown suffixin 46 of 638, across 4 files
  • load framework documentation using WebFetchin 45 of 638, across 3 files
  • verify each evaluation answer independentlyin 45 of 638, across 3 files
  • implement API client with authentication and paginationin 45 of 638, across 3 files
  • Define input schemas with validationin 27 of 638, across 9 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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