"Understanding File Systems" matching MCP servers:

Parses NACHA/ACH files into structured JSON and summaries, performing structural and arithmetic validation with IAT support, enabling automated file inspection and validation through MCP clients.

This MCP server enables database migration between heterogeneous systems (Oracle, PostgreSQL, SQL Server, Netezza to PostgreSQL or SQL Server) through AI assistants by providing tools for command preview, execution, validation, and workflow suggestions.

Resolves messy company, customer, and vendor names across CRM, ERP, and ITSM systems to canonical records using fuzzy matching, preventing AI agents from updating or creating wrong or duplicate records.

A tutorial implementation MCP server that enables analysis of CSV and Parquet files. Allows users to summarize data and query file information through natural language interactions.

MCP server that unifies real-time telemetry from industrial systems into a single queryable interface, enabling production visibility, anomaly detection, and operational insights.

Provides efficient handling of large Excel files through automatic chunking and pagination, using MCP to enable seamless file reading and management features such as sheet selection and error handling.

Enables comprehensive interaction with DHIS2 health information systems through 40+ tools covering complete Web API functionality. Supports data management, tracker programs, analytics, and bulk operations for DHIS2 development and administration.

Connects AI clients to the Matih data platform, enabling SQL queries, table profiling, analytics, chart creation, and file uploads through MCP tools with OAuth/PKCE authentication.

An MCP server that integrates Verodat's data management capabilities with AI systems like Claude Desktop, enabling users to manage accounts, workspaces, and datasets, as well as perform AI-powered queries on their data.

Enables AI applications to interact with decentralized storage through a standardized Model Context Protocol interface, allowing file uploads, retrievals, and identity management.

Connects MCP clients to databases like Snowflake, BigQuery, and Databricks through Alkemi's data platform, enabling natural language database queries with proper schema understanding and metadata management for consistent team-wide access.

Enables AI assistants to interact with Deephaven real-time data systems, allowing natural language queries, script execution, and management of both Community Core and Enterprise deployments for live data analysis and streaming workflows.

This read-only MCP Server allows you to connect to CSV Files data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for CSV Files (https://www.cdata.com/drivers/csv/download/mcp).

Enables AI agents to query live schema, lineage, and query-context across data warehouses, dbt projects, orchestration systems, and BI tools via MCP tools.

This MCP server enables AI-assisted professional profile generation by connecting to verified employee work data (skills, career history, certifications, projects) from employer HCM systems.

A server implementation of MCP for Apache Spark that provides query plans and catalog information to AI systems for query optimization and data discovery.

Converts legacy supply chain databases and file drops into MCP servers for AI agents, enabling direct interaction with closed systems via CLI.

Enables AI assistants to query unified commerce data from Amazon, Google Ads, GA4, and other selling systems using read-only SQL tools, with managed sync, freshness, and schema discovery.

Connect your business data to any MCP client. AgenticBI agents find the right data, join across systems, run queries, build dashboards, generate reports, and automate analytics workflows. No SQL required.

A Python-based MCP server that collects, analyzes, and visualizes forest fire occurrence data on maps, allowing users to access regional fire information, risk analysis, and map visualizations.