How do I handle large files in an MCP server?

The guide includes patterns for chunked streaming and asynchronous reading using Tokio to handle large resources without blocking the server.

What is the difference between MCP Tools and Resources?

Tools are actions that perform computations or modify state, while Resources are typically read-only data sources (like files or DB records) used to provide context to the AI.

Does this skill support caching for MCP resources?

Yes, it provides implementation patterns for both in-memory caching with TTL (Time To Live) and lazy loading to improve server performance.

What URI patterns should I use for MCP resources?

The guide recommends hierarchical paths (file:///path), query-style parameters (data://?id=1), or template-based URIs (user://{id}) for clear organization.

MCP Resources Guide for Rust

Name: MCP Resources Guide for Rust
Author: EmilLindfors

byEmilLindfors

Desarrollo de API

Guides developers in implementing Model Context Protocol (MCP) resources using the Rust rmcp crate for data-rich AI context.

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This skill provides expert guidance on building MCP resources, which are essential data sources that expose files, database records, and API responses to AI assistants. It covers the full implementation lifecycle in Rust, including URI design patterns, resource discovery, and MIME type handling. Developers will learn how to implement robust fetching strategies, advanced caching mechanisms like lazy loading, and efficient streaming for large datasets, ensuring that AI models have high-quality, structured context to work with.

Características Principales

Resource discovery and listing implementation via the rmcp crate
Advanced caching strategies including in-memory and lazy loading
Hierarchical and template-based URI design patterns
Implementation patterns for File System, Database, and API resources
Automatic MIME type detection and content handling
0 GitHub stars

Casos de Uso

Connecting external API data feeds directly to the Model Context Protocol
Exposing local source code and documentation as context for AI assistants
Providing read-only access to database records via structured URIs

Acerca de

Características Principales

Resource discovery and listing implementation via the rmcp crate
Advanced caching strategies including in-memory and lazy loading
Hierarchical and template-based URI design patterns
Implementation patterns for File System, Database, and API resources
Automatic MIME type detection and content handling
0 GitHub stars

Casos de Uso

Connecting external API data feeds directly to the Model Context Protocol
Exposing local source code and documentation as context for AI assistants
Providing read-only access to database records via structured URIs