"Understanding the concept of dependency" matching MCP servers:

Enables AI agents to discover and query data federated across MySQL/MariaDB, PostgreSQL, ClickHouse, S3 and Kafka with SQL, exposing tools to list databases, schemas, tables and connections, describe columns, search objects, inspect table statistics, run EXPLAIN, and execute arbitrary statements. It runs locally over stdio against a PostgreSQL-wire endpoint and returns structured results or SQLSTATE-coded errors.

MCP server that archives Decent DE1 espresso shots from Visualizer.coffee into SQLite and provides analysis tools for shots, beans, and profiles via MCP.

Enables AI agents to inspect schemas, walk Delta table history, run read-only DuckDB queries, and check data-quality and job-run status safely.

Enables AI agents to inspect, query, test, and safely fix dbt projects and BigQuery warehouses under policy-enforced controls, with read-only direct queries and dbt-only allowlisted writes.

Creates compact skeleton representations of large JSON files by preserving structure while truncating string values and deduplicating arrays, helping users understand JSON structure without processing the full data payload.

An MCP server that allows users to interact with YNAB data, enabling access to account balances, transactions, and the creation of new transactions through the Model Context Protocol.

Enables AI coding agents to import xlsx config tables, audit growth curves, run battle and gacha simulations, and reverse-engineer game spreadsheet formulas through 17 read-only tools backed by deterministic, zero-dependency pure-function engines.

Enables read-only exploration of SAP Datasphere tenants, letting users list spaces and modeling objects, read objects' raw CSN definitions, and trace upstream dependency graphs with evidence. It enforces read-only DEV/QAS/PRD access through the official SAP Datasphere CLI and OAuth, with no mutation, SQL, or arbitrary command capabilities.

A server that provides tools and utilities to support the implementation of Jij Modeling, featuring easy configuration and an extensible architecture for custom modeling workflows.

Enables structured document understanding of local PDFs via a dual-extract MCP server, combining MinerU text/layout and Qwen3-VL vision with fusion adjudication for field extraction, tables, formulas, and validation. Fully local and offline.

Enables natural language management of Apache Airflow workflows, including DAG monitoring, task control, and configuration, via the Model Context Protocol.

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.

Let LLMs analyze sensitive data safely by querying a tokenized, join-preserving copy of the database, with fail-closed PII scanning and provable numeric equivalence.

Enables processing and handling of weather-related data requests through the Model Context Protocol, providing meteorological information via a configured MCP server.

Bridges the Model Context Protocol to the Tabular Object Model, enabling natural language inspection, optimization, and authoring of DAX in Power BI Desktop.

A remote MCP server that exposes full Google Search Console data to AI assistants using Google's unrestricted Bulk Data Export instead of the limited API.

A server that connects to the Health Planet API to fetch and provide weight measurement data through any MCP-compatible client, allowing for retrieval and analysis of personal weight records.

Validates ISIN and CUSIP securities identifiers, and converts CUSIP to ISIN. Part of Pipeworx MCP gateway for financial data.

Enables AI agents and MCP-compliant clients to extract visual data from charts and graphs into structured markdown tables using deterministic, zero-dependency Python.

Generates a random number between 1 and 10 using the StupidAPIs service. Part of the Pipeworx MCP gateway providing access to 673+ data sources.