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Connects language models to a Qdrant vector database for storing and retrieving information.
Provides a universal database gateway implementing the Model Context Protocol (MCP) server interface.
Enables LLMs to inspect MySQL database schemas and execute read-only queries.
Provides a reactive database backend designed for web app developers to fetch data and perform business logic with strong consistency using TypeScript.
Enables secure interaction with MySQL databases through a Model Context Protocol (MCP) server.
Provides semantic memory and persistent storage capabilities for Claude using ChromaDB and sentence transformers.
Provides a reliable memory layer for AI applications and AI agents, enhancing response accuracy and reducing hallucinations.
Build AI applications that can learn and answer questions over large-scale federated data sources using a federated query engine.
Connects Supabase projects to AI assistants via the Model Context Protocol (MCP).
Supports developers and AI agents throughout the entire Postgres development process, from initial coding to production tuning.
Streamlines the integration of GenAI tools with databases by handling complexities like connection pooling and authentication.
Auto-loads databases in VS Code and provides affordances to aid development and debugging.
Builds and queries temporally-aware knowledge graphs tailored for AI agents operating in dynamic environments.
Provides a unified, cloud-native observability database for metrics, logs, and traces, supporting SQL, PromQL, and streaming analytics.
Create custom chatbots with personalized knowledge bases using advanced language models.
Empower ChatGPT with long-term memory by creating custom knowledge bases from uploaded documents and retrieving relevant answers using the OpenAI and Pinecone vector database stack.
Provides a developer-friendly, embedded retrieval engine for multimodal AI, enabling efficient search and data management.
Provides scalable, fast, and disk-friendly vector search capabilities directly within PostgreSQL.
Unify access to diverse data sources, from files and databases to popular applications, by querying them with SQL and integrating with large language models.
Empowers AI coding tools to generate robust, performant, and modern PostgreSQL code by providing deep, versioned expertise.
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