"Using Laravel Helper Functions and Resolving MySQL Table Query Errors" matching MCP servers:

A versatile tool that enables querying and exporting data from multiple relational databases (MySQL, PostgreSQL, Oracle, SQLite, etc.) in read-only mode for data safety.

Enables LLMs to query and analyze data across multiple MySQL databases with enterprise data federation, intelligent caching, cross-system analytics, and automated schema discovery for comprehensive business intelligence.

Paid remote MCP endpoint for AI SDK data queries, offering structured JSON tools, token-based access, usage receipts, and audit-ready workflow evidence.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables deterministic reconstruction of complex tables from OCR bounding-box payloads, recovering multi-column layouts, merged headers, and grid hierarchies. It also supports formula consistency auditing and sensitive PII redaction for document processing pipelines.

Enables deterministic reconstruction of complex tables from OCR bounding boxes, including multi-column layouts, merged headers, grid hierarchies, formula auditing, and PII redaction through MCP.

Logs LLM interactions to local CSV or Markdown files with automatic categorization for detailed tracking. It provides an interactive HTML dashboard to visualize query volume, model usage, and category distribution.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

An MCP server that enables AI coding assistants to interact with a local Airflow cluster via its REST API for triggering DAG runs, monitoring status, reading logs, and diagnosing errors.

A unified Model Context Protocol server for data engineering and analytics that lets LLM clients query, profile, transform, and visualize data using DuckDB and PySpark, while keeping raw data out of the model's context through read-only, bounded, and audited operations.

MCP server for CyberQuant data sharing platform that enables AI assistants to directly query and analyze financial data using CSV output for token efficiency.

Read-only SQL across PostgreSQL, MySQL, S3-compatible buckets and folders of Parquet, CSV and JSON files — and one query can join across all of them, federated in-process by DuckDB. Sources are given as connection strings at startup, and no tool writes: they are absent rather than disabled.

Enables agents to query curated metrics through a registry-backed semantic layer, preventing ad-hoc SQL and enforcing consistent definitions. Every numeric claim is verified against the underlying query result before it is allowed to be sent.