The Alpaca MCP server is a model context protocol (MCP) service that implements the Alpaca trading API, allowing large language models to interact with the Alpaca trading system through natural language, supporting stock/options trading, portfolio management, and real-time market data acquisition.

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).

WebMCP is a project that allows websites to support client-side LLMs (Large Language Models). It enables the sharing of tools, resources, and prompts between websites and LLMs through a local WebSocket server without the need for API keys and supports multiple models.

DINO-X MCP is a project that enables large language models to perform fine-grained object detection and image understanding through DINO-X and Grounding DINO 1.6 API. It can achieve precise object positioning, counting, attribute analysis, and scene understanding, and supports natural language-driven visual tasks and workflow integration.

HAProxy MCP Server is an HAProxy model context protocol server implemented in Go language. Through the HAProxy runtime API and the mcp-go library, it provides a standardized HAProxy management interface for large language models, supporting natural language interaction for load balancer management, monitoring, and traffic analysis.

HAL is an MCP server that provides HTTP API capabilities for large language models, supporting network requests through a secure interface and automatic generation of tools from OpenAPI specifications.

Rememberizer's MCP server provides the ability to interact with document and knowledge management APIs for large language models

The Excalidraw MCP Server is an integration tool that provides a drawing API for large language models, supporting the creation, modification, and management of Excalidraw charts, including element control, resource management, and team collaboration functions.

The Didlogic MCP Server is a service that implements the Model Context Protocol (MCP), providing a standardized interface for large language models (LLMs) to interact with the Didlogic API, and supporting multiple functions such as balance management and SIP account management.

Didlogic MCP Server is a model context protocol server that implements the Didlogic API, providing a standardized interface for large language models to access Didlogic services, including balance management, SIP account management, call record query, and other functions.

An MCP server application built on the Apache Superset REST API, enabling database query operations through large models

The ShotGrid MCP Rust client provides a complete implementation of the ShotGrid/Flow Production Tracking REST API and integrates the Model Context Protocol server, enabling large - language models to directly interact with ShotGrid.

An MCP server application built on the Apache Superset REST API, implementing database query functions through large models

The APISIX MCP Server is a tool that bridges large language models and the APISIX Admin API, supporting the management of APISIX resources through natural - language interaction.

This project converts the National Institute of Korean Language Standard Korean Dictionary API into an MCP protocol server, enabling large - language models to access and utilize Korean dictionary information.

The API-MARKET MCP Server is a model context protocol server that exposes over 200 API endpoints from API-Market as MCP resources, enabling large language models to discover and interact with them through the MCP protocol.

An MCP server that provides OpenAPI specification interaction services for large language models, supporting loading, exploring, and querying API structures

HAL is an MCP server that provides HTTP API capabilities for large language models, supporting network requests through a secure interface and automatic generation of tools from OpenAPI specifications.

File Context MCP is a TypeScript-based application that provides an API to query large language models (LLMs) through local file content. It supports multiple LLM providers (Ollama and Together.ai) and can process multiple file types to generate context-aware responses.

Implementation of the Feishu MCP Server, providing the ability for large AI models to interact with the Feishu API, mainly supporting bitable operations.