Top MCPs by Category

NCP is a unified MCP platform that consolidates 50+ tools, skills, and Photons into a single, intelligent interface. It enables code-mode execution, on-demand loading, scheduling, and semantic tool discovery, dramatically reducing token usage and latency while enabling AI assistants to work with external MCPs, skills, and Photons. This documentation covers how NCP works, the available MCPs and tools, installation and integration steps for popular clients (Claude Desktop, VS Code, and more), and practical examples that demonstrate how to find, run, and compose tools across MCPs. Whether you’re building with internal MCPs or exploring external tools, NCP provides a scalable, vendor-agnostic foundation for AI-powered automation and tool orchestration.

NCP is a unified MCP platform that consolidates 50+ tools, skills, and Photons into a single, intelligent interface. It enables code-mode execution, on-demand loading, scheduling, and semantic tool discovery, dramatically reducing token usage and latency while enabling AI assistants to work with external MCPs, skills, and Photons. This documentation covers how NCP works, the available MCPs and tools, installation and integration steps for popular clients (Claude Desktop, VS Code, and more), and practical examples that demonstrate how to find, run, and compose tools across MCPs. Whether you’re building with internal MCPs or exploring external tools, NCP provides a scalable, vendor-agnostic foundation for AI-powered automation and tool orchestration.

MindsDB ships with a built-in MCP (Model Context Protocol) server that enables MCP applications to connect, unify and respond to questions over large-scale federated data. It spans databases, data warehouses, and SaaS applications, allowing you to query across diverse sources in a unified manner. The MCP server is integrated into MindsDB's architecture with the Connect-Unify-Respond philosophy, and you can learn more about MCP at docs.mindsdb.com/mcp/overview. You can install MindsDB Server via Docker Desktop or Docker, and the MCP server is part of the standard MindsDB deployment.

MindsDB ships with a built-in MCP (Model Context Protocol) server that enables MCP applications to connect, unify and respond to questions over large-scale federated data. It spans databases, data warehouses, and SaaS applications, allowing you to query across diverse sources in a unified manner. The MCP server is integrated into MindsDB's architecture with the Connect-Unify-Respond philosophy, and you can learn more about MCP at docs.mindsdb.com/mcp/overview. You can install MindsDB Server via Docker Desktop or Docker, and the MCP server is part of the standard MindsDB deployment.

MindsDB ships with a built-in MCP (Model Context Protocol) server that enables MCP applications to connect, unify and respond to questions over large-scale federated data. It spans databases, data warehouses, and SaaS applications, allowing you to query across diverse sources in a unified manner. The MCP server is integrated into MindsDB's architecture with the Connect-Unify-Respond philosophy, and you can learn more about MCP at docs.mindsdb.com/mcp/overview. You can install MindsDB Server via Docker Desktop or Docker, and the MCP server is part of the standard MindsDB deployment.

MetaMCP is a MCP proxy that lets you dynamically aggregate MCP servers into a unified MCP server, and apply middlewares. MetaMCP itself is a MCP server so it can be easily plugged into ANY MCP clients. It functions as an MCP Aggregator, Orchestrator, Middleware, and Gateway all in one docker image, enabling scalable, configurable hosting of multiple MCP servers behind a single endpoint with flexible authentication, tooling, and annotations. This README introduces core concepts such as MCP Server configurations, Namespaces, Endpoints, Middleware, Inspector, and Tool Overrides & Annotations, and provides quick-start guidance for running MetaMCP with Docker, building a development environment, and integrating with clients like Claude Desktop via proxies. It also covers MCP protocol compatibility, authentication options (including API keys, OAuth, and OIDC), and integration guidance for developers looking to remix MCP tool flows and middleware pipelines.

MetaMCP is a MCP proxy that lets you dynamically aggregate MCP servers into a unified MCP server, and apply middlewares. MetaMCP itself is a MCP server so it can be easily plugged into ANY MCP clients. It functions as an MCP Aggregator, Orchestrator, Middleware, and Gateway all in one docker image, enabling scalable, configurable hosting of multiple MCP servers behind a single endpoint with flexible authentication, tooling, and annotations. This README introduces core concepts such as MCP Server configurations, Namespaces, Endpoints, Middleware, Inspector, and Tool Overrides & Annotations, and provides quick-start guidance for running MetaMCP with Docker, building a development environment, and integrating with clients like Claude Desktop via proxies. It also covers MCP protocol compatibility, authentication options (including API keys, OAuth, and OIDC), and integration guidance for developers looking to remix MCP tool flows and middleware pipelines.

MetaMCP is a MCP proxy that lets you dynamically aggregate MCP servers into a unified MCP server, and apply middlewares. MetaMCP itself is a MCP server so it can be easily plugged into ANY MCP clients. It functions as an MCP Aggregator, Orchestrator, Middleware, and Gateway all in one docker image, enabling scalable, configurable hosting of multiple MCP servers behind a single endpoint with flexible authentication, tooling, and annotations. This README introduces core concepts such as MCP Server configurations, Namespaces, Endpoints, Middleware, Inspector, and Tool Overrides & Annotations, and provides quick-start guidance for running MetaMCP with Docker, building a development environment, and integrating with clients like Claude Desktop via proxies. It also covers MCP protocol compatibility, authentication options (including API keys, OAuth, and OIDC), and integration guidance for developers looking to remix MCP tool flows and middleware pipelines.

MetaMCP is a MCP proxy that lets you dynamically aggregate MCP servers into a unified MCP server, and apply middlewares. MetaMCP itself is a MCP server so it can be easily plugged into ANY MCP clients. It functions as an MCP Aggregator, Orchestrator, Middleware, and Gateway all in one docker image, enabling scalable, configurable hosting of multiple MCP servers behind a single endpoint with flexible authentication, tooling, and annotations. This README introduces core concepts such as MCP Server configurations, Namespaces, Endpoints, Middleware, Inspector, and Tool Overrides & Annotations, and provides quick-start guidance for running MetaMCP with Docker, building a development environment, and integrating with clients like Claude Desktop via proxies. It also covers MCP protocol compatibility, authentication options (including API keys, OAuth, and OIDC), and integration guidance for developers looking to remix MCP tool flows and middleware pipelines.

MetaMCP is a MCP proxy that lets you dynamically aggregate MCP servers into a unified MCP server, and apply middlewares. MetaMCP itself is a MCP server so it can be easily plugged into ANY MCP clients. It functions as an MCP Aggregator, Orchestrator, Middleware, and Gateway all in one docker image, enabling scalable, configurable hosting of multiple MCP servers behind a single endpoint with flexible authentication, tooling, and annotations. This README introduces core concepts such as MCP Server configurations, Namespaces, Endpoints, Middleware, Inspector, and Tool Overrides & Annotations, and provides quick-start guidance for running MetaMCP with Docker, building a development environment, and integrating with clients like Claude Desktop via proxies. It also covers MCP protocol compatibility, authentication options (including API keys, OAuth, and OIDC), and integration guidance for developers looking to remix MCP tool flows and middleware pipelines.

Claude Skills MCP Server is an MCP server that enables intelligent search and retrieval of Claude Agent Skills using vector embeddings and semantic similarity. It implements a progressive disclosure architecture so AI applications can discover and load skills in stages (metadata → full content → files) while remaining fast and local. The server can load skills from multiple sources, including Official Anthropic Skills, K-Dense AI Scientific Skills, and local directories, providing a zero-configuration experience out of the box for Cursor or standalone usage. The architecture is split into a lightweight frontend and a heavy backend, enabling instant startup and background backend download, with no API keys required and the ability to connect to remote hosted backends if desired.

Claude Skills MCP Server is an MCP server that enables intelligent search and retrieval of Claude Agent Skills using vector embeddings and semantic similarity. It implements a progressive disclosure architecture so AI applications can discover and load skills in stages (metadata → full content → files) while remaining fast and local. The server can load skills from multiple sources, including Official Anthropic Skills, K-Dense AI Scientific Skills, and local directories, providing a zero-configuration experience out of the box for Cursor or standalone usage. The architecture is split into a lightweight frontend and a heavy backend, enabling instant startup and background backend download, with no API keys required and the ability to connect to remote hosted backends if desired.

Claude Skills MCP Server is an MCP server that enables intelligent search and retrieval of Claude Agent Skills using vector embeddings and semantic similarity. It implements a progressive disclosure architecture so AI applications can discover and load skills in stages (metadata → full content → files) while remaining fast and local. The server can load skills from multiple sources, including Official Anthropic Skills, K-Dense AI Scientific Skills, and local directories, providing a zero-configuration experience out of the box for Cursor or standalone usage. The architecture is split into a lightweight frontend and a heavy backend, enabling instant startup and background backend download, with no API keys required and the ability to connect to remote hosted backends if desired.

Claude Skills MCP Server is an MCP server that enables intelligent search and retrieval of Claude Agent Skills using vector embeddings and semantic similarity. It implements a progressive disclosure architecture so AI applications can discover and load skills in stages (metadata → full content → files) while remaining fast and local. The server can load skills from multiple sources, including Official Anthropic Skills, K-Dense AI Scientific Skills, and local directories, providing a zero-configuration experience out of the box for Cursor or standalone usage. The architecture is split into a lightweight frontend and a heavy backend, enabling instant startup and background backend download, with no API keys required and the ability to connect to remote hosted backends if desired.

Neurolink includes an External MCP Server capability, enabling seamless integration with external Model Context Protocol (MCP) servers. This feature loads and manages external MCP servers from a dedicated configuration file (.mcp-config.json), enables real JSON-RPC based communication, and supports end-to-end tool execution within the NeuroLink platform. It is designed for multi-provider AI workflows, allowing providers to delegate tool execution to external servers while preserving type safety, robust error handling, and deterministic behavior. The documentation highlights how to configure external MCP servers, register and discover tools, and perform end-to-end tool execution through the CLI, ensuring a production-ready MCP ecosystem.

Neurolink includes an External MCP Server capability, enabling seamless integration with external Model Context Protocol (MCP) servers. This feature loads and manages external MCP servers from a dedicated configuration file (.mcp-config.json), enables real JSON-RPC based communication, and supports end-to-end tool execution within the NeuroLink platform. It is designed for multi-provider AI workflows, allowing providers to delegate tool execution to external servers while preserving type safety, robust error handling, and deterministic behavior. The documentation highlights how to configure external MCP servers, register and discover tools, and perform end-to-end tool execution through the CLI, ensuring a production-ready MCP ecosystem.

Neurolink includes an External MCP Server capability, enabling seamless integration with external Model Context Protocol (MCP) servers. This feature loads and manages external MCP servers from a dedicated configuration file (.mcp-config.json), enables real JSON-RPC based communication, and supports end-to-end tool execution within the NeuroLink platform. It is designed for multi-provider AI workflows, allowing providers to delegate tool execution to external servers while preserving type safety, robust error handling, and deterministic behavior. The documentation highlights how to configure external MCP servers, register and discover tools, and perform end-to-end tool execution through the CLI, ensuring a production-ready MCP ecosystem.

Neurolink includes an External MCP Server capability, enabling seamless integration with external Model Context Protocol (MCP) servers. This feature loads and manages external MCP servers from a dedicated configuration file (.mcp-config.json), enables real JSON-RPC based communication, and supports end-to-end tool execution within the NeuroLink platform. It is designed for multi-provider AI workflows, allowing providers to delegate tool execution to external servers while preserving type safety, robust error handling, and deterministic behavior. The documentation highlights how to configure external MCP servers, register and discover tools, and perform end-to-end tool execution through the CLI, ensuring a production-ready MCP ecosystem.

Neurolink includes an External MCP Server capability, enabling seamless integration with external Model Context Protocol (MCP) servers. This feature loads and manages external MCP servers from a dedicated configuration file (.mcp-config.json), enables real JSON-RPC based communication, and supports end-to-end tool execution within the NeuroLink platform. It is designed for multi-provider AI workflows, allowing providers to delegate tool execution to external servers while preserving type safety, robust error handling, and deterministic behavior. The documentation highlights how to configure external MCP servers, register and discover tools, and perform end-to-end tool execution through the CLI, ensuring a production-ready MCP ecosystem.

Neurolink includes an External MCP Server capability, enabling seamless integration with external Model Context Protocol (MCP) servers. This feature loads and manages external MCP servers from a dedicated configuration file (.mcp-config.json), enables real JSON-RPC based communication, and supports end-to-end tool execution within the NeuroLink platform. It is designed for multi-provider AI workflows, allowing providers to delegate tool execution to external servers while preserving type safety, robust error handling, and deterministic behavior. The documentation highlights how to configure external MCP servers, register and discover tools, and perform end-to-end tool execution through the CLI, ensuring a production-ready MCP ecosystem.