"Web scraping tools and techniques for data extraction" matching MCP servers:

A governed MCP server enabling LLM agents to query BigQuery, inspect GCS, trigger Airflow DAGs, and run data-quality checks with built-in security guardrails like allow-lists, cost ceilings, and audit trails.

Enables LLMs to extract content from websites using automated static and dynamic scraping engines with built-in anti-bot protections. It provides tools for web data retrieval and stores results in MongoDB with support for JSON and CSV exports.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.

Connect any AI to PostgreSQL, MySQL, or SQL Server — 24 dialect-aware tools for query, schema, optimization, and more.

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

Enables Claude or any MCP-capable assistant to explore and query a small business's sales, payments, invoices, and expenses through read-only SQL tools, while personal-data columns and write operations are refused by the database policy.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

Enables teams to structure metric definitions, compare semantic differences, detect JOIN fanout and drift, reconcile mismatched numbers layer by layer, and persist metric contracts as YAML.

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

An MCP server with 66+ tools for data engineering, enabling AI assistants to interact with Kafka, databases, AWS, data pipelines, infrastructure, and more.

MCP server for Grubhub Data Platform operations, providing 40+ tools across 18 service categories for data platform management, observability, analytics, and collaboration.

Enables agents to discover, inspect, and query municipal open datasets from data.seattle.gov through Socrata SODA2, with bounded reads, aggregates, and reference guidance.

Model Context Protocol (MCP) server providing access to 155 normalized Japanese public open datasets (10.16M+ records) including GEPS procurement, healthcare, land prices, and DuckDB SQL.

An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.

Enables AI agents to discover, request access to, and query data products in Data Mesh Manager, enforcing governance policies while retrieving business data from platforms like Snowflake and Databricks.

Read-only MCP server for querying ClickHouse (product telemetry) and Elasticsearch (download analytics), built for Percona VISTA.

MCP server providing AI assistants access to Polish public registries (KRS, CEIDG) and statistical data (GUS BDL) for querying companies, sole proprietorships, and regional statistics.

Enables agents to explore a database safely and read-only through three tools — list_tables, describe_table, and run_query — served over stdio. Queries are guarded by lexical validation, a capped LIMIT, a read-only SQLite connection, and an authorizer with a timeout.

MCP data connector for Jazz v2 alpha servers, providing schema discovery and query/read tools with optional mutation capabilities for application data.

Enables AI clients to search and read over 2,400 New York City public datasets through the Socrata SODA API, with ready-made tools for restaurant health inspections and 311 service requests plus general dataset discovery and querying.

Lets AI agents and developers inspect and query local MySQL, Redis, and MongoDB instances over STDIO or authenticated loopback HTTP, with read-only defaults and allowlisted non-production writes that require explicit opt-in. Production connections always reject writes, and database-enforced read-only accounts are recommended.

Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.

An MCP server for internal data platforms that enables search, viewing, tracing, and read-only querying of business assets like dashboards, metrics, and events.

Exposes SQL Server and Snowflake schema metadata to AI coding agents, enabling schema search, join path discovery, and stored procedure metadata retrieval without live queries.

An MCP server for interacting with SQL Server databases that enables schema inspection, record counting, and paginated data retrieval. It provides tools to explore table structures and fetch specific records while enforcing safety limits on data volume.

A SQL Server CLI and MCP server for Claude Code that supports standard SQL Server authentication for database interaction and management. It enables users to perform schema exploration, execute queries, and manage data records with built-in SQL injection prevention.

Enables answering questions about Ukrainian open data from the data.gov.ua CKAN portal by searching datasets, inspecting resource schemas, and running read-only SQL aggregates over a single tabular resource. Every data-backed answer is computed from retrieved data and returned with machine-readable provenance, and unsupported or unanswerable requests are refused rather than guessed.