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Connects language models to an OpenSearch database for semantic memory storage and retrieval.
Enables AI models to execute SQL queries on Snowflake databases through the Model Context Protocol.
Logs statistically unusual events in conversations to a SQLite database for later analysis.
Facilitates interaction with SingleStore databases, enabling querying, schema exploration, and ER diagram generation.
Implements the Model Context Protocol for ArangoDB to facilitate interaction with ArangoDB instances.
Enables interaction with Databricks workspaces via the Model Context Protocol (MCP).
Provides a Model Context Protocol (MCP) server for interacting with Vertica databases.
Enables interaction with MySQL databases via the Model Context Protocol (MCP).
Enables natural language search and data analysis within OpenSearch by integrating LangChain agents.
Enables AI agents to interact with Alibaba Cloud PolarDB-X databases through a Model Context Protocol (MCP) server.
Provides a comprehensive Model Context Protocol (MCP) server for accessing the STRING protein interaction database, enabling powerful tools for protein network analysis, functional enrichment, and comparative genomics.
Enables AI applications to execute SQL queries against databases via the Model Context Protocol.
Transforms text and web content into structured knowledge graphs using local AI models, with persistent storage and real-time visualization.
Provides a low-latency, clustered key-value store with HTTP and WebSocket interfaces, designed for cloud-native deployment.
Provides a standardized interface for SQLite database interactions, enabling schema introspection, query execution, and database modifications.
Integrates Claude with Obsidian notes for semantic and full-text search capabilities.
Enables AI assistants to securely interact with PostgreSQL databases through the Model Context Protocol, offering extensive administration, observability, and querying capabilities.
Enable AI assistants to interact with SQL databases including SQLite, PostgreSQL, and MySQL safely and efficiently.
Unifies cloud-based semantic search with real-time web search augmentation for RAG applications.
Enables natural language querying and interaction with rasdaman databases by exposing its functionality as tools to Large Language Models.
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