Servidores MCP

Connects AI agents to ChromaDB vector databases for semantic search and retrieval augmented generation (RAG) workflows. Supports creating collections, upserting documents with embeddings, querying by semantic similarity, and managing metadata filters. Ideal for knowledge base and document retrieval applications.

Official Snowflake MCP server enabling AI agents to query and analyze data in the Snowflake AI Data Cloud. Supports running SQL against warehouses, exploring databases and schemas, describing tables, and invoking Cortex AI services for search and analytics, with role-based access control honored end to end.

Official MCP server for the Neo4j graph database. Enables AI agents to run Cypher queries, inspect graph schemas, and manage nodes and relationships. Includes support for natural-language to Cypher translation and graph-backed memory for agents. Useful for knowledge graphs, recommendations, fraud detection, and relationship-heavy data.

MCP server for DuckDB, the fast in-process analytical database. Lets AI agents run analytical SQL over local files (CSV, Parquet, JSON), attach databases, inspect schemas, and profile queries. Ideal for ad-hoc data analysis, ETL prototyping, and querying large columnar files without a separate database server.

MCP server for the Weaviate open-source vector database. Enables AI agents to store objects, run semantic and hybrid searches, and manage collections, making it a memory and retrieval backend for RAG applications directly from AI-powered tools.

MCP server for the Railway deployment platform. Lets AI agents create projects and services, deploy from repositories, manage environment variables, view deployment logs, and inspect service status. Useful for provisioning backends, databases, and cron jobs and for debugging deploys directly from an AI assistant.

Official MCP server for the Milvus vector database. Lets AI agents create collections, insert vectors, and run similarity and scalar-filtered searches over large-scale embedding data, enabling retrieval and long-term memory for AI applications.

Official DigitalOcean MCP server for managing cloud infrastructure. Lets AI agents deploy and manage App Platform apps, Droplets, databases, and Spaces object storage, and read logs and metrics. Useful for provisioning and operating cloud resources and debugging deployments through an AI assistant.

Metabase's built-in MCP server that lets AI clients connect directly to a Metabase instance, scoped to the connecting user's permissions. Enables agents to discover databases and models, run queries, and retrieve results and dashboards so teams can ask questions of their business intelligence data in natural language.

Pinecone's official MCP server connects AI assistants to Pinecone vector databases for retrieval-augmented generation (RAG) workflows. Lets agents create and configure indexes, upsert and embed documents, and run semantic searches over vector data — all from natural language, without leaving the editor or chat.