Design an MCP Server to Expose Internal Tools to an Agent
Plan a Model Context Protocol server that safely exposes your internal data and actions as tools an agent can call.
Get a concrete MCP server design — tools, resources, auth, and limits — so agents in Claude, Claude Code, or other MCP clients can use your systems.
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Prompt objective
Get a concrete MCP server design — tools, resources, auth, and limits — so agents in Claude, Claude Code, or other MCP clients can use your systems.
Real use case
A company wants Claude Code and their internal assistant to query the orders database and create support tickets, but only through a controlled, auditable interface rather than raw DB access.
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Prompt
Act as an engineer who builds Model Context Protocol (MCP) servers. Design an MCP server that exposes the capabilities below to AI agents. Systems to expose: [DATABASES, APIS, ACTIONS] Who the clients are: [E.G. CLAUDE DESKTOP, CLAUDE CODE, INTERNAL AGENT] Security constraints: [AUTH, PII, WRITE LIMITS] Produce: 1. Tool list: for each MCP tool, the name, description the model will see, input schema (JSON), output shape, and whether it is read or write. 2. Resources/prompts the server should also expose, if any. 3. Auth model: how the server authenticates the caller and scopes what each caller can do. 4. Guardrails on write tools: confirmation steps, rate limits, allowlists, and dry-run support. 5. Error contract: how tool errors are returned so the agent can recover gracefully. 6. An audit/logging plan for every tool invocation. 7. The descriptions and schemas written so a model reliably picks the right tool (clear names, no overlap, examples in the description). Keep write access minimal and explicit. Note any tool that should require human confirmation.
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How to use this prompt
- 1Replace the key placeholders first: DATABASES, APIS, ACTIONS, E.G. CLAUDE DESKTOP, CLAUDE CODE, INTERNAL AGENT, AUTH, PII, WRITE LIMITS.
- 2Replace any bracketed placeholders like [this] with your own context.
- 3Add extra background information when you want more tailored results.
- 4Combine multiple prompts in one conversation when you need a richer output.
- 5Save your best-performing prompts so they are easy to reuse later.
Next best step
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A guide for technical builders choosing between prompts, coding workflows, and agent-based implementation.
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