More screenshots
Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+22 moreClaude CodeCursorCodex CLIMuseDots
OpenClaw
Manus
Grok
Grok Bot+18 agentsmcp server design
Design and deploy secure, scalable Model Context Protocol (MCP) servers for LLM tool and resource integration.
$3
mcp server design
Example session with this skill installed
Design an MCP server to interface with a internal Postgres DB. I need to search tables, get schemas, and run safe select queries. How should I structure the tools and resources?
- Read your context and instructions
- Compiled the mcp server design
I have designed the MCP server architecture for your Postgres interface. This structure prioritizes safety and model steerability by separating structural metadata from data execution.
Postgres MCP Server Design
| Component | Type | Description |
|---|---|---|
db://schema/{table} | Resource | Returns the DDL and column metadata for a specific table. |
list_tables | Tool | Lists all available tables in the public schema with brief descriptions. |
search_data | Tool | Executes a SELECT with mandatory LIMIT and specific column filters. |
query_wizard | Prompt | A template that asks the user for a goal and suggests a sequence of queries. |
Implementation Specification
// Tool definition for safe data retrieval
{
name: "search_data",
description: "Search specific rows in a table. Always use this for data retrieval.",
inputSchema: {
type: "object",
properties: {
table: { type: "string", description: "Table name" },
columns: { type: "array", items: { type: "string" } },
filter: { type: "string", description: "Simple WHERE clause fragments" },
limit: { type: "integer", default: 50, maximum: 200 }
},
required: ["table", "columns"]
}
}
// Resource URI implementation
// URI: db://schema/users
// MIME Type: application/json
{
"table": "users",
"columns": [
{"name": "id", "type": "uuid"},
{"name": "email", "type": "varchar(255)"}
]
}
Next steps
- Implement the
search_datatool using a read-only database user to enforce safety at the DB level. - Use the MCP Inspector to verify that
db://URIs resolve correctly. - Add a
resources/updatednotification to the schema resource to trigger when migrations occur.
Connects securely to your tools. The creator never sees your data.
About this skill
Stop writing bespoke wrappers every time you need an LLM to talk to a new database, API, or internal tool. This skill provides the technical architecture and design patterns required to build Model Context Protocol (MCP) servers that work across Claude Desktop, Cursor, VS Code, and custom agent runtimes. It eliminates the friction of tight coupling between your agent logic and your data sources by implementing a standardized communication layer.
What it does
- Primitive Mapping helps you correctly categorize capabilities into Tools for autonomous action, Resources for read-only context, and Prompts for templated workflows.
- Transport Architecture guides the implementation of stdio for local IDE extensions and Streamable HTTP for remote, multi-tenant deployments.
- Security Enforcement provides patterns for OAuth 2.1 integration, dynamic client registration, and server-side authorization to prevent unauthorized tool execution.
- Schema Optimization ensures your tool and resource descriptions are written for high model steerability and accurate parameter extraction.
- Reliability Design implements progress notifications for long-running operations and cancellation handling to manage server resources.
How it works
- Model your domain by mapping your system's functions to the appropriate MCP primitives (Tools, Resources, or Prompts).
- Define the interface using JSON Schema fields for tool arguments and stable URI patterns for resources.
- Implement transport by configuring the server to handle stdio for local development and Streamable HTTP for production scaling.
- Harden the bridge by applying server-side validation, audit logging, and PII redaction to all incoming model requests.
Frameworks & tools
This skill is designed for the official MCP SDKs in TypeScript (@modelcontextprotocol/sdk) and Python. It targets integrations for Claude Desktop, Cursor, Zed, and VS Code.
Why this beats prompting it yourself
Generic prompts often lead to "mega-tools" that confuse models or insecure implementations that lack proper auth. This skill enforces strict architectural rules, like statelessness and transport-agnostic logic, ensuring your server remains stable as you scale.
Use cases
- Expose internal Jira or GitHub Enterprise data to an engineering agent.
- Build a standardized interface for an internal SQL data warehouse.
- Decouple agent toolsets from the runtime to support multiple IDEs.
- Create multi-step diagnostic wizards using parameterized MCP prompts.
Known limitations
Does not cover building the LLM clients themselves. Focuses on the server-side implementation and the interface between the client and the data source.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
Reviews
No reviews yet
Be one of the first to try it. Every listed skill passes our trust checks below.
Security scanned
Passed our 8-point scan before listing
Fresh listing
Recently published to Agensi
Money-back guarantee
Doesn't do what its page promises? You get your money back.
Trust & safety
Security scanned
Verified clean 3 days ago
- Passed all security checks, Safe to install
Requires