The Supabase MCP Server is a tool that connects Supabase projects with AI assistants. It standardizes the interaction between large language models (LLMs) and external services through the Model Context Protocol (MCP), enabling functions such as database management, configuration acquisition, and data querying.

K8M is an AI-driven lightweight Kubernetes console tool that integrates large model capabilities, supports multi-cluster management, and provides MCP services.

MCP2Lambda is an MCP protocol server that runs AWS Lambda functions as tools for large language models (LLMs). AI models can call Lambda functions to access private resources and AWS services without code modification.

The Wikipedia MCP Server is a tool that provides Wikipedia information query services for large language models. It enables real - time data access through a standardized protocol interface and includes functions such as searching, article retrieval, and summary generation.

The Qiniu Cloud MCP service is a model context protocol server built on Qiniu Cloud products, supporting AI large model clients to access Qiniu Cloud storage, intelligent multimedia services, and CDN functions.

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.

GraphRAG MCP is a hybrid retrieval system that combines the Neo4j graph database and the Qdrant vector database, providing document retrieval services that combine semantics and graph relationships for large language models.

The PlayFab MCP Server is a middleware that enables large language models to directly interact with PlayFab services, realizing data query and management functions.

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

An MCP server that provides documentation query services for Ant Design components, allowing large language models to explore and understand the Ant Design component library through dedicated tools.

An MCP server that provides GraphQL schema exploration services for Large Language Models, supporting the loading, querying, and analysis of GraphQL schema files.

The BigQuery MCP Server is a protocol server that provides Google BigQuery access services for large language models, supporting functions such as query execution, dataset management, and table structure analysis.

SMCP Proxy is a reverse proxy designed for Model Context Protocol (MCP) services, providing a security layer with OIDC authentication, supporting enterprise - level authentication and authorization, and simplifying standardized interactions with large language models (LLMs).

The GeoServer MCP Server is a server - side implementation of the Model Context Protocol (MCP) that connects large language models (LLMs) with the GeoServer REST API, enabling AI assistants to interact with geospatial data and services.

The OLS MCP Server is a tool that provides ontology query services for large - language models. By connecting to the EBI Ontology Query Service API, it helps AI assistants accurately obtain ontology terms, concepts, and hierarchical structures in the biomedical field.

A Python - based Model Context Protocol (MCP) server template for creating standardized large language model (LLM) context services.

YDB MCP is a tool that provides Model Context Protocol services for the YDB database, supporting interaction with large language models through the MCP protocol to enable natural language database operations.

The Model Context Protocol (MCP) is a standardized protocol introduced by Anthropic for the interaction between large language models (LLMs) and external tools and functions, as well as for injecting context into LLMs. It enables models to request real-time information, perform operations in external systems, access professional knowledge bases, and interact with APIs and services. The MCP is similar to a USB hub, serving as a standard interface that reduces the risk of API changes because each MCP server is maintained by its own company, and users only need to integrate it. The MCP server provides three functions: tools, resources, and prompts.

The Model Context Protocol (MCP) is an open-source protocol designed to enable Large Language Models (LLMs) to seamlessly interact with external tools, services, and data sources through a standardized interface, simplifying the integration process and expanding AI capabilities.

The MCP Server is a server that implements the Model Context Protocol, supporting standardized interaction between large language models and external tools and services, providing support for multiple tools, RESTful APIs, and automated documentation.