"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 exploring and querying SQLite databases through natural language, with tools to list tables, describe table structures, and run SELECT queries.

An MCP server that enables AI agents to interact with SQLite databases by querying schemas, executing SQL, and inspecting table metadata. It supports safe database access through configurable read-only modes, query timeouts, and dry-run execution plans.

Query, explore, and manage SQLite databases through the Model Context Protocol. Connect any MCP-compatible AI client to your databases.

Read-only SQLite database explorer for MCP clients. Allows discovery of tables and columns via resources and running SELECT queries via a tool.

A Model Context Protocol server that enables SQL operations (SELECT, INSERT, UPDATE, DELETE) and table management through a standardized interface with SQLite databases.

A graph-friendly relational server that stores project memory, tasks, and metadata in a centralized SQLite database as the authoritative source of truth. It enables AI agents to manage complex project states through entity-relationship modeling and can generate human-readable markdown views on demand.

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

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

A Model Context Protocol server that enables AI assistants to interact with SQLite databases by connecting to database files, listing tables, describing schemas, and executing queries.

Enables AI models to interact with SQLite Cloud databases, supporting SQL queries, schema management, and performance analysis.

Implements a Model Context Protocol server that enables natural language interactions with SQLite databases, providing tools to list tables, retrieve schemas, count rows, and execute read-only SQL queries.

A Model Context Protocol server implementation that enables AI assistants to execute SQL queries and interact with SQLite databases through a structured interface.

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

Enables AI agents to query Korean listed companies' financial statements, public disclosures, executive information, and shareholder structures in real-time using the DART API.

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, compare, and get detailed information about MCP servers from the mcpcatalogs.com directory.

Search and retrieve detailed information about Swiss companies from the official Zefix register, including company profiles, corporate structures, and SHAB publications.

MCP server that lets AI assistants query current, dated information about PatientNotes, an AI medical scribe, covering pricing, features, languages, compliance, and competitor comparisons.

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.