Stores and retrieves information using the Qdrant vector search engine, enabling semantic search for relevant data. It functions as a memory layer for AI applications accessing external tools and information.

Connect Supabase projects with AI assistants for managing tables, fetching configurations, and querying data efficiently. Enables seamless integration of AI capabilities directly into application workflows.

Integrates vector database capabilities for managing collections, performing semantic searches, and retrieving data with advanced filtering. Enhances AI models with powerful data retrieval features to improve context and performance.

Universal MCP server tailored for databases, facilitating secure and compliant interactions optimized for large language models and AI agents. It supports a variety of database systems including PostgreSQL, MySQL, and ElasticSearch among others.

Interact with Neon serverless Postgres databases using natural language for tasks such as database creation and management, running SQL queries, handling migrations, and managing projects.

Connects Claude to databases for querying and analysis, facilitating SQL query writing, visualization of table relationships, and report generation.

Provides access to MongoDB databases for large language models, enabling inspection of collection schemas and execution of read-only queries.

Provides read and write access to Airtable databases, enabling interaction with database schemas and record manipulation.

Connect to Elasticsearch or OpenSearch clusters for natural language interaction, enabling operations such as searching documents, managing indices, and monitoring cluster health.

Read and write to a Pinecone index from a compatible MCP client like Claude Desktop, facilitating data interaction and retrieval.

A Model Context Protocol server for managing AWS resources, specifically focused on S3 and DynamoDB operations. It automatically logs all interactions for audit purposes.

Interact with Meilisearch to manage indices and documents, configure settings, monitor tasks, and handle API keys. It supports dynamic connections to multiple Meilisearch instances and offers smart search capabilities across indices.

Connects AI assistants to StarRocks databases for executing SQL queries and exploring database schemas with ease. Provides capabilities for data visualization and detailed data overview retrieval without complex setups.

Provides operations for interacting with MySQL databases through a standardized interface for AI models.

Interact programmatically with Airtable's API for managing bases, tables, fields, and records, facilitating structured data management and creation processes.

Integrates with Neo4j graph database to perform graph database operations through natural language interactions.

Facilitates secure interaction with OceanBase databases, allowing users to list tables, read data, and execute SQL queries through a controlled interface.

Access Azure Data Explorer clusters and databases through standardized MCP interfaces to execute KQL queries and explore data resources. Features include querying capabilities, resource discovery, and support for authentication.

Provides vector database capabilities for semantic search and document management, enabling storage and retrieval of documents along with their metadata.

Execute SQL queries against AWS Athena databases and retrieve the results for analysis and reporting.

Seamlessly interact with a Nocodb database to perform CRUD operations on its tables using the Model Context Protocol. Manage data efficiently with functionalities for adding, updating, deleting, and retrieving records.

Retrieve and analyze data or run tasks using an in-memory SQLite database for efficient data processing. Supports data interaction through a Developer API with an ETL pipeline for handling data requests and queries.

Leverage Unity Catalog functions within LLM applications to execute, manage, and automate tasks directly from agents. Integrate data workflows with powerful catalog capabilities.

Access and manage InfluxDB time-series data, execute queries, write data, and utilize templates for common operations. Provides resources for organization, bucket, and measurement data management.

Execute SQL queries and manage databases, including interaction with Kafka topics and Iceberg tables. Offers a user-friendly interface and robust backend capabilities for efficient data workflows.