"Connecting to PostgreSQL database, retrieving table schema, and executing SQL queries" matching MCP servers:

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

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

Enables deterministic SQL query synthesis from tabular schemas and query verification via MCP, with zero external dependencies.

A Model Context Protocol server that enables LLMs like Claude to interact with SQLite and SQL Server databases, allowing for schema inspection and SQL query execution.

Enables LLM agents to access Global Database's company intelligence, including company profiles, financials, ownership, people search, prospecting, and KYB/compliance lookups against official registries.

Provides read-only SQL Server health diagnostics (server health, blocking queries, missing indexes) via MCP, with a GUI installer that automatically configures AI clients like Claude Desktop.

Enables MCP clients such as GitHub Copilot, Codex, Claude... to explore a SQL Server 2017+ database read-only: databases, schemas, tables, views, procedures, functions, indexes and dependency graphs, plus filtered, grouped, sampled and paginated queries capped by row limits.

This read-only MCP Server allows you to connect to PostgreSQL data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

An open-source, local-first MCP server for automated Schema.org JSON-LD generation, GA4 metric validation, /llm.txt auditing, and content stickiness analytics.

Enables AI clients to interact with PostgreSQL databases through natural language, translating requests into structured queries and returning results via a secure self-hosted server.

Enables multimodal OCR-based extraction of table grids and merged cells into Markdown with deterministic, zero-dependency execution through MCP for AI agents.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Enables autonomous web form inspection and schema auto-mapping by matching input attributes, autocomplete hints, and regex validations to agent state, while also pruning DOMs and converting tables into structured JSON for web agents.

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.

GenPark MCP server for normalizing and translating structured data schemas.

Enables AI agents and MCP clients to heuristically parse multi-column document dumps, aligned spacing, and CSV/TSV input, converting them into clean GitHub Flavored Markdown tables and typed JSON. Runs fully offline on the Python standard library with zero external dependencies, returning deterministic results without LLM round-trips.

Enables AI agents and MCP clients to convert ASCII/OCR text dumps, aligned spacing, and CSV/TSV data into clean GitHub Flavored Markdown tables and typed JSON deterministically.

Enables agents to deterministically extract structured entities from input payloads and validate or coerce them against JSON schemas, returning a standardized response dossier with execution telemetry. It runs as a zero-dependency MCP server that plugs into Claude Desktop, Cursor, and other MCP clients.