Okta Integration
Enables LLM agents to interact with and manage Okta organizations through its Admin Management APIs.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables LLM agents to interact with and manage Okta organizations through its Admin Management APIs.
Enables Claude Desktop to interface with an Ollama LLM server.
Facilitates advanced MCP server setup using uv, llama-index, ollama, and Cursor IDE for AI agent orchestration and RAG pipelines.
Adapts MCPO tools to be used as Ollama-compatible functions.
Enables web scraping, content extraction, and Google search with structured data.
Integrates Omeka S API with Claude Desktop using the Model Context Protocol (MCP).
Generates images using the OhmyGPT Flux API.
Provides utilities for managing miniapps, orchestrator applications, and dialog logs within the Omilia Cloud Platform.
Provides a self-hostable server for automatic license plate recognition via REST and Model Context Protocol APIs.
Integrates OmniFocus with Claude Desktop, enabling advanced task management and GTD methodologies through natural language commands.
Enhances OmniFocus with complete subtask support, comprehensive perspective views, advanced task filtering, and seamless Claude AI integration for intelligent task management.
Accepts todo requests via FastMCP and stores them in MongoDB.
Unifies access to multiple mcpservers through a single all-in-one entrance.
Provides a proxy for accessing commercial and non-commercial MCP servers, enabling unified authentication, discounted rates, and revenue sharing for AI agents and API providers.
Provides a Model Context Protocol (MCP) server for managing OneSignal applications and interacting with the OneSignal API.
Provides programmatic access to Swiss legal commentaries for search and retrieval through Model Context Protocol (MCP) compatible clients.
Enables network control and management capabilities through the ONOS SDN controller.
Connects Claude to GraphDB's SPARQL endpoint and Ollama models via a Model Context Protocol (MCP) server.
Facilitates searching and querying documentation and GitHub code examples for the Onyx programming language.
Connects Generative AI systems to multiple Kubernetes clusters for streamlined management and observability.
Provides a dynamic discovery server for enterprise infrastructure, offering hot-reloadable tool registries, a pluggable marketplace, and secure multi-transport communication inclu…
Provides 33 specialized, enterprise-grade search and research tools for Claude Desktop, featuring robust security and comprehensive data access.
Manages todos and integrates with Google Calendar using natural language through OpenAI's Assistant API and Model Context Protocol (MCP).
Enables AI assistants to generate images through the OpenAI DALL-E API with fine-grained control.
MCP (Model Context Protocol) servers are tools that connect AI assistants like Claude, Cursor, and other AI coding tools to external data sources, APIs, and services. They enable AI models to access real-time information, execute code, interact with databases, and perform actions beyond their base capabilities. Check out our curated collection of the best MCP servers for Cursor →
MCP servers act as intermediaries between AI assistants and external systems. When you ask Claude or Cursor to perform a task requiring external data, the MCP server handles the request, fetches the data, and returns it in a format the AI can understand and use.
When selecting an MCP server, consider:
For detailed setup guides, see our Complete MCP Server Setup Guide →
Everything you need to know about installing, using, and troubleshooting Model Context Protocol.
To install MCP servers in Cursor: 1) Open Cursor settings (Cmd+,), 2) Navigate to MCP Servers section, 3) Click 'Add Server', 4) Enter server configuration (name and command), 5) Restart Cursor. Check out our curated collection of the best MCP servers for Cursor with detailed setup guides.
MCP servers are protocol-level integrations that work across multiple AI assistants (Claude, Cursor, etc.), while VS Code extensions are editor-specific. MCP servers provide context to AI models, whereas extensions add IDE functionality. MCP is more portable and AI-focused.
Most MCP servers listed are open-source and free. Some enterprise connectors (like Salesforce or Jira) may require paid API access to the underlying service, but the MCP server code itself is usually free.
Yes! The Model Context Protocol is open standard. You can build servers in Python or TypeScript/Node.js to expose your own internal APIs or databases to Claude and Cursor.
An MCP server is a lightweight program that exposes specific capabilities (data access, tool execution, prompts) to AI assistants through a standardized protocol. MCP servers allow Claude and other AI models to securely interact with external systems like databases, APIs, file systems, and web services while maintaining security boundaries.
MCP servers connect to Claude Desktop or other MCP-compatible clients through a standardized JSON-RPC protocol. When you configure an MCP server in Claude Desktop, Claude can access its resources (data/content), use its tools (functions to execute), and leverage its prompts (templated interactions). The protocol ensures secure, controlled access to external capabilities.
Essential MCP servers for beginners include: Filesystem (local file access), SQLite/PostgreSQL (database queries), GitHub (repository access), Brave Search (web search), and Memory (persistent context). These cover common use cases and have excellent documentation. Start with 2-3 servers and expand based on your needs.
Most MCP servers install via npm (npx) or Python (uvx/pip). Configure them in Claude Desktop's config file (claude_desktop_config.json) by specifying the command, arguments, and any required environment variables like API keys. Our directory links to each server's documentation with specific installation instructions.
MCP servers run locally on your machine with explicit permissions you configure. They can only access resources you authorize, and Claude cannot bypass these boundaries. However, always review server code, use official/verified servers when possible, limit permissions to what's necessary, and be cautious with servers that request broad access.
Resources are data sources Claude can read (files, database results, API responses). Tools are functions Claude can execute (run queries, send messages, create files). Prompts are pre-defined templates for common interactions. Most MCP servers expose one or more of these capability types.
MCP is supported by Claude Desktop (official), Cursor IDE, Continue (VS Code extension), and various community implementations. The protocol is open, so support is expanding to more AI development tools. Check our compatibility filters to find servers tested with your preferred client.
Our MCP servers directory is updated weekly with new servers, documentation improvements, and compatibility updates. We monitor GitHub releases, community contributions, and Anthropic announcements to ensure our listings reflect the latest MCP ecosystem developments.