# LLM interaction

The MCP Python SDK is a Python library that implements the Model Context Protocol (MCP), used to standardize the interaction between LLM applications and servers, supporting the exposure and management of resources, tools, and prompts.

The MCP Python SDK is a Python library that implements the Model Context Protocol (MCP) for standardizing the interaction between LLM applications and servers, supporting the exposure and management of resources, tools, and prompts.

A Model Context Protocol (MCP) tool implemented in Python, used to handle communication between applications and large language models (LLMs), and obtain the exchange rates of specified currencies against the Swedish Krona through the Riksbanken API.

An intelligent bot that integrates MCP servers with Slack, providing LLM - driven interaction and tool execution capabilities.

The StateSet MCP Server is a model context protocol service used to integrate with StateSet's issue operating system, enabling LLMs to interact with StateSet.

Metis MCP Tools is a repository containing multiple toolkits, aiming to enhance the functions of Metis RAG applications. These tools provide functions such as database management, vector storage operations, document processing, and LLM interaction, and enable language models to interact with external resources through the standardized Model Context Protocol (MCP).

This project is a Go implementation of the Model Context Protocol (MCP), a JSON-RPC based protocol for client-server interaction in LLM applications. The project includes Go structure definitions, client implementation, and example code, supporting interaction with resources, tools, prompts, etc.

The Telegram MCP Server is a Node.js-based service that allows LLMs to send notifications and receive user responses via Telegram and supports integration with MCP-compatible applications such as Cline.

mcpx-py is a Python library for interacting with LLMs through the mcp.run tool. It supports multiple AI models and provides structured output functionality.

This project is a personal and public knowledge base about the Model Context Protocol (MCP), aiming to explain and explore the working principles, interaction processes, and tool call mechanisms of MCP, including example code, concept analysis, and reference materials.

The MCP server for AdsPower browser's LocalAPI, supporting browser creation and configuration operations through LLM instructions.

This is a Docker-based Python server template that implements the Model Context Protocol (MCP), built with the FastMCP library, and supports real-time interaction with large language models (LLMs) through Server-Sent Events (SSE).

The MCP server of the DealX platform provides a standard interface for LLMs to interact with the DealX platform and currently supports the ad search function.

ScreenPilot is a tool that enables LLMs to fully control the device through an MCP server. It provides a screen automation toolkit and supports functions such as screen capture and mouse and keyboard control. It is suitable for automation, education, and entertainment.

Documentation library for the MCP Python SDK, providing documentation for the Python development toolkit of the Model Context Protocol (MCP), including usage guides and API references for the FastMCP server framework.

An MCP client application based on Streamlit, supporting connection to multiple LLM providers (such as OpenAI, Anthropic, etc.) and interaction with MCP servers, providing tool testing and chat interface functions.

A GameBoy emulator server based on the MCP protocol that allows LLMs to control console operations through tools

kuri is a Rust framework for building Model Context Protocol (MCP) servers, focusing on developer experience and code clarity. It supports defining tools and prompts through simple macros to enable interaction between LLMs and the external world.

A simple OpenDigger MCP server that allows LLMs to obtain OpenDigger data and provide data analysis insights through the MCP tool.

A TypeScript-based development template for Model Context Protocol (MCP) applications, providing standardized components such as resources, tools, and prompts, supporting multiple transport protocols, and used to build secure services for interacting with LLMs.

The MCP protocol standardizes the interaction between applications and LLMs, and realizes unified management of tool invocation, resource access, and prompt templates through a modular architecture (server, client, host). This project demonstrates how to build an MCP server and client that support knowledge base queries, context selection, and analysis processes.

MCP is an open-source protocol for standardizing LLM interactions, providing a unified framework for connecting data sources, obtaining context, using tools, and executing standard prompts. Project examples demonstrate how to build MCP servers and clients to implement knowledge base chatbot functionality.