Engineering Advanced MCPOpenAPIServers

MCP Server Builder

Build MCP servers from OpenAPI specs with manifest validation.

$skillfish add ~skills/mcp-server-builder

Real Conversations

See how the MCP Server Builder skill responds to actual requests. These are representative examples of what your AI agent will produce.

You

We have an internal billing service that wraps the Stripe API. The OpenAPI spec is 340 endpoints. I need to expose about 20 of them as MCP tools so our AI agents can create subscriptions, list invoices, and issue refunds. How do I do this without hand-writing 20 tool definitions?

Agent

This is exactly what the scaffold script is for. Point it at your spec and filter to the endpoints you need.

This skill includes executable scripts — I'll need your permission before running them.

The workflow:

python3 scripts/openapi_to_mcp.py \
  --input billing-api.json \
  --server-name billing-mcp \
  --language python \
  --output-dir ./out \
  --format text

For 340 endpoints, the script generates the full manifest but you'd filter to your 20 by keeping only the operations with these operationId values:

  • createSubscription, listSubscriptions, cancelSubscription
  • listInvoices, getInvoice, voidInvoice
  • createRefund, listRefunds

Tool naming the script enforces:

  • POST /v1/subscriptionscreate_subscription (not post_v1_subscriptions)
  • Every tool gets a verb-first name from the operationId

What you'll get in out/:

  • tool_manifest.json — 20 tool definitions with input schemas
  • server.py — starter FastMCP server with stub handlers

Before wiring up real Stripe calls, run the validator:

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

The validator flags missing descriptions (agents pick tools poorly without them), ambiguous required fields, and naming issues. Destructive tools like cancel_subscription and create_refund need an explicit confirm: bool parameter to prevent accidental execution — the validator will catch if those are missing.

Get Started

How to install and use this skill in your preferred environment.

Skills are designed for AI coding agents (Claude Code, Cursor, Windsurf) and IDE-based workflows where the agent can read files, run scripts, and act on your codebase. Web-based AI can use the knowledge and frameworks, but won't have tool access.

Models & Context

Which AI models and context windows work best with this skill.

Recommended Models

Best
Claude Opus 4 Claude Sonnet 4 GPT-4.1 Gemini 2.5 Pro Grok 3 Kimi K2
Good
Claude Haiku 4.5 GPT-4.1 mini Gemini 2.5 Flash Grok 3 mini

Larger models produce more detailed, production-ready outputs.

Context Window

This skill's SKILL.md is typically 3–10 KB — fits in any modern context window.

8K Skill only
32K+ Skill + conversation
100K+ Skill + references + codebase

All current frontier models (Claude, GPT, Gemini) support 100K+ context. Use the full window for complex multi-service work.

Pro tips for best results

1

Be specific

Include numbers — users, budget, RPS — so the skill can size the architecture.

2

Share constraints

Compliance needs, team size, and existing stack all improve the output.

3

Iterate

Start with a high-level design, then ask follow-ups for IaC, cost analysis, or security review.

4

Combine skills

Pair with companion skills below for end-to-end coverage.

Ready to try MCP Server Builder?

Install the skill and start getting expert-level guidance in your workflow — any agent, any IDE.

$skillfish add ~skills/mcp-server-builder
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