Iceberg

MySQL Schema Explorer

Empower artificial intelligence to navigate and engage with MySQL database structures for documenting, constructing queries, and analyzing schemas without the need for direct database entry.

Databricks

Discover deeper insights and analyze data effortlessly by leveraging the Statement Execution API within an integrated environment like Databricks. Seamlessly execute SQL queries, explore schema listings, and delve into table structures for enhanced data exploration and analysis capabilities.

AIStor

Connect and engage with MinIO AIStor repositories for seamless interaction.

PostgreSQL

Explore PostgreSQL databases effortlessly with Model Context Protocol (MCP), offering seamless AI integration, multi-database compatibility, comprehensive schema insights, and confidential read-only transactions. Safeguard sensitive connection data while ensuring efficient data querying.

Apache IoTDB

Easily interact with Apache IoTDB time-series databases by utilizing a secure interface based on Python. Perform queries, view tables, and explore schemas effortlessly.

Atlan Data Catalog

Facilitates seamless communication between artificial intelligence agents and Atlan data catalog functionalities for tasks such as searching, accessing, exploring lineage, and modifying asset metadata using the pyatlan Software Development Kit (SDK).

Trino (SQL Query Engine)

Enhance your AI applications by linking them to Trino/Iceberg databases for efficient SQL processing, data investigation, and table enhancement. Seamlessly manage connections and navigate catalogs for a streamlined experience.

DuckDB

Leverage the capability of AI systems to retrieve and scrutinize information using DuckDB, a specialized in-memory database designed for handling complex analytical tasks efficiently. This database is tailored for OLAP operations, offering seamless compatibility with various file formats such as CSV, Parquet, and JSON, and facilitating access to external data repositories like S3.

Apache Iceberg

Explore Apache Iceberg tables on AWS effortlessly with the Model Context Protocol (MCP). Gain direct insights into catalogs, schemas, properties, and partition details without the need for intricate queries or coding.

Databricks

Facilitates seamless connectivity between AI applications and Databricks environments, allowing streamlined access to data repositories, schema structures, tables, and SQL databases to support efficient querying and data analysis within Databricks datasets.

Apache Pinot

Unlock the power of real-time analytics with seamless integration to Apache Pinot. Conduct SQL queries, analyze table schemas, inspect segments, and access cluster metadata for enhanced operational oversight and business intelligence insights.

Elasticsearch

Enhance your AI-powered applications with enhanced search functionality, data access, and analytical tools by seamlessly connecting to Elasticsearch through the Model Context Protocol (MCP). Unlock advanced search features and streamline data analysis for optimized performance.

DataBridge

Enhance connectivity with DataBridge for seamless integration with local databases, facilitating efficient data ingestion and retrieval to empower AI solutions with reliable storage capabilities.

Apache Iceberg

Access and manage Apache Iceberg tables seamlessly using a SQL interface connected to Iceberg REST catalogs and S3-compatible storage. Facilitating data exploration in data lakes without the need to change workflows, this protocol empowers data analysts with efficient querying capabilities.

Apache Gravitino

Enhance your data exploration and management capabilities with seamless integration into Apache Gravitino. Gain convenient access to metadata services for efficient catalog browsing, schema management, table organization, and user role assignments without disrupting your workflow.