Solon AI Embedded Examples
Provides embedded examples for Solon AI MCP (Micro Control Plane) server implementations.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides embedded examples for Solon AI MCP (Micro Control Plane) server implementations.
Extracts IDL files from closed-source Solana smart contracts and decompiles them using an AI-powered platform.
Enables AI assistants to control Sonic Pi programmatically through OSC messages.
Plays a sound when Cursor AI completes a task to provide audio feedback.
Enables AI assistants like Claude Desktop to directly interact with source code files and project directories for enhanced development workflows.
Enables AI models to interact with SourceSync.ai's knowledge management platform through a standardized Model Context Protocol (MCP) server.
Provides structured project specification management capabilities for AI editors through a specification-driven development workflow.
Runs a Model Context Protocol (MCP) server over stdio for Specif-ai.
Enables local speech-to-text functionality for Claude Code on Linux, integrating voice input directly into the AI's conversation stream.
Orchestrates language model interactions and tool executions using the Model Context Protocol (MCP).
Enables AI models to interact with Spinnaker deployments, pipelines, and applications through the Model Context Protocol (MCP).
Enables AI agents to create, read, modify, and convert Excel workbooks independently of Microsoft Office.
Control Spotify playback and library directly from your terminal or through AI assistants.
Exposes data through a Spring Boot application acting as an MCP server, enabling secure two-way connections between data sources and AI-powered tools.
Provides user management tools for AI assistants via a Model Context Protocol (MCP) server.
Connects AI models to real-time information about SpringOne conference sessions and speakers using the Model Context Protocol (MCP).
Provides a dynamic, agent- and LLM-friendly SQLite memory bank for structured data management and knowledge graphs.
Connects Squad, an AI-powered product discovery platform, to large language models.
Demonstrates a Server-Sent Events (SSE) server failing with Bun runtime while succeeding with Node.js.
Facilitates seamless management of multiple SSH connections, remote command execution, and file transfers directly from Claude Code.
Monitors domain registration and SSL certificate expiration dates.
Provides a structured foundation for leveraging Cursor AI's advanced features, including Single Source of Truth (SSOT), project rules, and Model Context Protocol (MCP), within sof…
Empowers AI agents to interact with the Starknet blockchain, query data, manage wallets, and engage with smart contracts.
Surfaces early go-to-market activity by analyzing changelogs, sitemaps, and product pages to power launch detection, founder/investor intelligence, and agent workflows.
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.