"Understanding File Structures" matching MCP servers:

An MCP server that provides persistent memory for database schemas by storing table structures and metadata in a local SQLite file. It enables LLMs to save, retrieve, and manage database snapshots to maintain a structured understanding of database architectures.

A Model Context Protocol server that enables LLMs to understand BigQuery dataset structures and execute SQL queries.

A Model Context Protocol server that provides DLIS (Digital Log Interchange Standard) file analysis capabilities. This server enables LLMs to extract information from DLIS files, including channel data and metadata, with support for hierarchical data structures.

Enables MySQL database operations through MCP, including executing SQL queries, listing databases and tables, and describing table structures.

Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.

Enables AI assistants to directly query MySQL databases, list tables, and view table structures through natural language.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

Enables AI agents to analyze databases through MCP, including listing all tables and inspecting table structures.

MCP server for exploring metadata of corporate databases: table structures, relationships, dependencies, and export to UML diagrams.

Enables querying SAP Business One HANA databases through direct SQL, including read-only safeguards and tools for inspecting schemas, tables, and table structures.

A Model Context Protocol server providing tools for DB queries, API calls, file I/O, and text transformations, enabling AI agents like Claude to perform real-world actions.

Marker-indexed SQL cache MCP server that indexes in-file @scry.\* markers into a SQLite database, enabling agents to query structured project knowledge via read-only SQL without LLM reasoning.

Enables AI assistants to interact with Hadoop Hue for executing SQL queries using Hive, SparkSQL, or Impala and managing HDFS files. It supports directory browsing, file transfers, and exporting query results to CSV through the Model Context Protocol.

Enables an AI assistant to read form structures and submissions from a Coletum account (read-only) and to produce Excel/CSV exports, Coletum-style or user-template PDFs, and photographic reports on request. It also stores preferences such as logo and company name and reports where each generated file was saved.

Query only the data you need from your JSON file and keep your context clean

Enables managing PocketBase instances through intent-first tools for schema inspection, record CRUD, bulk operations, authentication, file handling, and server monitoring, with optional destructive operations gated behind explicit opt-in.

A read-only MCP server that exposes SQL database access to LLMs, supporting multiple database types, compact columnar results, pagination, and file export.

Enables read-only MySQL database connectivity, allowing execution of SELECT queries, listing tables, and describing table structures via natural language.

A Model Context Protocol (MCP) server that exposes tools for exploring and querying SQLite and PostgreSQL databases. It allows Large Language Models (LLMs) to inspect table structures, perform statistical profiling, generate entity-relationship diagrams, and execute queries safely.

Enables users to provision, manage, and query AI-native Postgres databases directly from MCP-compatible clients using x402 micropayments. It supports executing SQL, performing REST API interactions via PostgREST, and managing database leases and file storage.