Explore 'client' MCP Resources

A lightweight client for interacting with LLMs, supporting OpenAI and compatible APIs with MCP extension.

A Node.js MCP client that simplifies interaction with MCP servers using convenient methods for common operations.

AppDog generates MCP servers from OpenAPI specifications, streamlining API development and deployment.

A Dart implementation of MCP enabling AI agent interactions with server and client components.

Swift-based MCP implementation for AI agent interactions with server and client components supporting protocol standard.

A Python package for generating typed API clients and MCP servers from OpenAPI specifications.

Rust library for building discoverable networks of AI agents with peer discovery and resource sharing.

EasyMCP is a high-performance Python SDK for managing multiple MCP servers with caching and namespace support.

A TypeScript-based client connecting to MCP servers, enabling AI interaction with DeepSeek or OpenAI models.

A simple Spring Boot-based MCP client demonstration utilizing the spring-ai-mcp-client-spring-boot-starter.

AIMCP AIME is an AI-powered multi-client platform that enables efficient management of AI models and services.