MCP Tool Designer Prompt
Turn a plain-English capability list into a clean MCP tool schema.
/ quick answer
Feed this to Claude or GPT-5 with the capability list of your internal system. Output is a starting schema for an MCP server. Turn a plain-English capability list into a clean MCP tool schema.
You are an MCP server architect. I will describe a data source and the actions we want AI clients to take against it. Return:
1) A list of `tools` (name, description, JSON schema for inputs, expected output shape).
2) A list of `resources` (URI template + description).
3) A list of `prompts` we should expose.
4) Auth model (stdio/local, HTTP+OAuth, API key).
5) Guardrails: which tools must be read-only, rate-limited, or human-approved.
Be strict: every tool must be minimal, composable, and have a clear success/failure contract.
Data source: {{DESCRIPTION}}
Desired capabilities: {{CAPABILITIES}}## tools
- `search_customers` (input: {query, limit}) — returns top matching customers (read-only)
- `get_customer` (input: {id}) — returns full customer record (read-only)
.../ frequently asked
What does the MCP Tool Designer Prompt prompt do?
Feed this to Claude or GPT-5 with the capability list of your internal system. Output is a starting schema for an MCP server.
Which AI models work with this prompt?
It is model-agnostic: it works with any capable general model. Replace the bracketed variables with your own context before running it.
How do I use this prompt?
1) Copy the prompt with the copy button. 2) Replace every bracketed variable with your real details. 3) Paste it into your AI assistant. 4) Compare the answer with the example output and ask for changes if needed.
What output should I expect?
## tools - `search_customers` (input: {query, limit}) — returns top matching customers (read-only) - `get_customer` (input: {id}) — returns full customer record (read-only) ...
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →MCP (Model Context Protocol)
Open standard letting AI clients call external tools, data and prompts.
- →Tool Calling
The model-to-system interface that lets an LLM trigger external actions.
- →Tool Use
An LLM invoking external functions to act beyond text generation.
Related workflows
Turn this into a repeatable process.
- →Build an MCP Server for Your Internal Data
Expose one internal data source to every AI client via the Model Context Protocol.
- →Audit MCP Tool Security
A checklist that catches the failure modes unique to model-driven tool calls.
Related tool stacks
The tools that run it in production.
- →AI Automation Operator Stack
The default toolset for one operator running multiple AI-powered business workflows.
Related prompts
Reusable prompts for this job.
- →MCP Tool Surface Design Prompt
Turns an app description into a minimal, safe MCP tool and resource surface.
- →Prompt Improver Prompt
Iterate a weak prompt into a strong one using best practices.
- →Strategic Analyst Prompt
Turn a business situation into a McKinsey-style strategic memo.
- →Buyer Persona Builder Prompt
Generate a detailed persona from a product description and target market.
Related use cases
How people apply it, and what came out.
- →Consultancy Ships a Client-Wide MCP Server in 2 Weeks
A boutique AI consultancy replaces 6 bespoke Zapier flows with one MCP server.
Comparisons & alternatives
Pick between the options.
- →OpenAI vs Anthropic for Agents
Which provider builds better production agents in 2026.