Explore our complete collection of MCP servers to connect AI to your favorite tools.
Integrates Google Workspace services with AI assistants and applications via the Model Context Protocol.
Auto-loads databases in VS Code and provides affordances to aid development and debugging.
Connects Slack workspaces to Model Context Protocol (MCP) for enhanced integration with AI models.
Provides semantic memory and persistent storage capabilities for Claude using ChromaDB and sentence transformers.
Enables collaboration between small, on-device LLMs and larger cloud-based models for cost-efficient language processing.
Demonstrates security vulnerabilities in Model Context Protocol (MCP) implementations for educational purposes.
Connects MCP clients that only support local (stdio) servers to a remote MCP server, enabling authentication support.
Autonomously evaluates web applications by deploying a browser-driving agent directly from your code editor.
Fetches and converts Deepwiki content to Markdown for use in code editors and other MCP-compatible clients.
Enables interaction with Text to Speech and video/image generation APIs through the Model Context Protocol (MCP).
Automates the evaluation and debugging of web applications using a browser-powered agent directly within your code editor.
Provides a robust and scalable operating system foundation for building, deploying, and managing intelligent AI agents.
Connects a Zotero research library with AI assistants to facilitate searching and discussing research papers.
Integrates Azure DevOps capabilities directly into development environments by providing a local server that enables interaction with various services.
Integrates Google Analytics APIs with a local Model Context Protocol (MCP) server to provide LLM-consumable tools for analytics data.
Autonomously evaluates web applications using LLM-powered agents within a code editor.
Compose data sources into a unified graph using this GraphQL Federation platform.
Connects language models to a Qdrant vector database for storing and retrieving information.
Enables advanced automation and interaction capabilities for Infrastructure as Code (IaC) development through integration with Terraform Registry APIs.
Enables AI agents to measure, exchange, and settle value on-chain within a decentralized network.
Connects AI agents with Azure services, enabling exploration, querying, and management of Azure resources.
Integrates JADX decompiler with Model Context Protocol (MCP) for AI-powered static code analysis and real-time reverse engineering.
Enables interaction with Text to Speech and audio processing APIs for MCP clients.
Converts existing RESTful and gRPC services into MCP-Server compatible services without infrastructure changes.
Facilitates the integration of AI models into daily workflows through agent-based frameworks and command-line tools.
Enables developers to write Model Context Protocol servers and clients in Go with minimal code.
Integrates Tavily's search and data extraction capabilities with AI assistants via the Model Context Protocol.
Enables LLMs to inspect MySQL database schemas and execute read-only queries.
Provides intelligent build analysis and visualization for Rspack and webpack projects, making the build process transparent and optimizable.
Integrates AI models into Ruby applications via the Model Context Protocol.
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