# LLM integration

The MuseScore MCP server is a protocol service that connects MuseScore with LLM clients, supporting basic music creation through natural language, such as adding notes, deleting, creating tuplets, etc.

A NodeJS-based MySQL MCP server that provides read-only database access capabilities, supporting LLMs to query the database structure and execute read-only queries.

The Neon MCP Server is a server based on the Model Context Protocol (MCP) standard, used to manage the context interaction between large - language models (LLMs) and the Neon database. It supports performing database operations through natural language instructions, such as creating projects, managing branches, running SQL queries, and migrations.

The Browserbase MCP Server is an open - source project based on the Model Context Protocol (MCP), providing cloud browser automation capabilities, supporting web page interaction, data extraction, screenshot taking, and JavaScript execution, etc., to help LLM applications seamlessly integrate with external data sources and tools.

The Nostr MCP Server is a service that provides Nostr network interaction capabilities for LLMs such as Claude, supporting functions such as obtaining user profiles, notes, long - form content, and tipping records.

Anki MCP Server is a protocol server that enables interaction between LLM and the Anki flashcard software through the AnkiConnect API, supporting functions such as creating decks, adding notes, and searching for cards.

The Alby Bitcoin Payments MCP Server is a service that integrates a Bitcoin Lightning Network wallet with an LLM via Nostr Wallet Connect (NWC), supports the LNURL and L402 protocols, and provides both local and remote connection methods.

An MCP server that connects to a ClickHouse database, supporting data analysis through natural language queries and integrating with LLMs such as Claude.

The NiFi MCP project provides a chat interface based on natural language interaction, allowing users to interact with Apache NiFi instances through LLM models, supporting querying, documenting, and operating NiFi components.

This project is an MCP service for PostgreSQL, providing read-only access to the database, supporting query execution and schema viewing, and suitable for LLM integration.

MCP Go is a server-side framework for the Model Context Protocol (MCP) implemented in Go, used to connect LLM applications with external data sources and tools. It provides core functions such as resource management, tool invocation, and prompt templates, and supports session management and middleware extension.

A PHP-based tool for quickly building MCP servers, supporting the creation of tools, exposure of resources, and definition of prompts, simplifying LLM context management.

An RSS crawler server based on the MCP protocol, used for crawling and managing RSS subscription content and integrating with LLM.

A server project that allows LLMs to directly access Google Sheets data via the MCP protocol

A Kubernetes management server based on the MCP protocol that enables control of Kubernetes clusters through natural language interaction.

Tutorial on integrating MCP servers with LLM applications

MCP Firebird is a service that implements the Anthropic Model Context Protocol (MCP) for the Firebird database, allowing large language models such as Claude to securely access and analyze database content.

MCP Firebird is a service that implements the Anthropic Model Context Protocol (MCP) for Firebird databases, allowing LLMs to securely access and manipulate databases.

An example project of an MCP server demonstrating how to chat with DeepSeek and use MCP tool calls.

The Scrapeless MCP Server is an open - source protocol project that seamlessly integrates LLM applications with external data sources and tools (such as Google Search) in a standardized way, providing dynamic context retrieval capabilities.

Provide a virtual machine environment based on Magalu Cloud, enabling code execution and virtual resource interaction through the Model Context Protocol (MCP). Support the secure integration of LLMs with sandboxed VMs to enhance agent capabilities.

Model Context Protocol (MCP) .NET sample library, demonstrating how to use the MCP protocol to standardize the context interaction of large language models (LLMs) in .NET applications. It includes examples such as a YouTube subtitle extractor, supports flexible switching of LLM providers, and enables the construction of AI workflows.

The Logfire MCP server is a model context protocol service based on OpenTelemetry, which provides the ability for LLM to access application telemetry data and supports exception tracing and custom SQL queries.

An Alpaca trading MCP server implemented in Python, allowing large language models (such as Claude) to interact with the Alpaca trading API through the standardized Model Context Protocol, supporting functions such as account management, market data query, and trading operations.

The MCP server is used for the integration service of large language models (LLMs).

An MCP service for retrieving and analyzing Sentry issues, supporting the retrieval of a single event or a list of project events, facilitating LLM analysis or processing.

The Kagi MCP Server is a tool that integrates Kagi's search and summarization APIs, providing web search and content summarization functions for large - language models, and supporting multiple communication protocols and API key management.

Todoist MCP Server Extended is a server implementation that integrates Claude or other MCP - compatible LLMs with Todoist, manages tasks through natural language, and optimizes the workflow efficiency of LLM.

The MCP Command Server is a secure system command execution service designed specifically for LLM applications such as Claude, providing a controlled command execution environment.

The arXiv MCP Server is a service based on the Model Context Protocol (MCP) that allows users to interact with the arXiv API using natural language, enabling functions such as retrieving academic article metadata, downloading PDF files, searching the database, and loading articles into the context of a large - language model (LLM).