"Information about SQLite databases" matching MCP servers:

Enables LLMs and agents to interact with relational databases (SQL Server, MySQL, PostgreSQL) through MCP tools. Supports executing queries, inserting records, listing tables, and exposing database schemas with secure credential management.

Enables AI agents to query and explore SQLite databases through schema inspection, arbitrary SQL execution, and predefined canned queries. Compatible with Datasette metadata for enriching database structure with descriptions.

A Python-based SQLite MCP server supporting database read/write operations with natural language interaction capabilities, packaged for Docker deployment in stdio mode.

Offline RAG MCP server that indexes documents into SQLite with hybrid vector and lexical search, and enables natural language queries via Claude.

Enables AI agents to store, search, update, and manage local long-term memories with namespaces, tags, expiration, and audit trails, without requiring cloud accounts, API keys, or network access.

A Model Context Protocol (MCP) server implementation that provides database interaction and business intelligence capabilities through SQLite. This server enables running SQL queries, analyzing business data, and automatically generating business insight memos.

A server that exposes SQLite database operations as tools, allowing natural language interactions with a database through LlamaIndex and Ollama LLM integration.

Simple, fast, long-term memory for your AI chatbots, agents, and MCP tools. Give your LLM a persistent memory using a local SQLite file. No complex database servers, no heavy cloud setup, and zero C++ compilation errors. Works everywhere.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

MCP Server for SurrealDB - Bridge AI assistants with SurrealDB databases

Query SQL databases (SQLite, PostgreSQL, BigQuery, Databricks) in natural language through a business semantic layer — glossary, metrics, and a data dictionary grounded against your real schema. Read-only by default, with an embedded SQLite + sqlite-vec metadata store and no external infra required.

Enables AI assistants to search and ask questions about documents stored in AnythingLLM workspaces through MCP tools.

Enables AI assistants to search and retrieve transcripts from the Entra.Chat podcast about Microsoft Entra ID, with timestamped YouTube links and guest information.

Local-first MCP memory server that gives AI coding agents long-term memory via SQLite and sqlite-vec, with optional LLM-powered layering. No gateway or API key required.

Enables AI agents to securely query databases (PostgreSQL, SQLite, MySQL, DuckDB) with read-only defaults and multi-layer SQL injection prevention.

An MCP server that provides read-only access to MySQL databases.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

A Model Context Protocol server that allows AI agents to perform WHOIS lookups, enabling users to directly ask the AI about domain availability, ownership, registration details, and other domain information.

Provides LLMs with specialized knowledge about fountain pen inks, enabling intelligent ink search, color matching, and recommendations through various tools.

A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.