"Browsing websites and reading their content" matching MCP servers:

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 convert a vendor partner directory (such as PartnerPage or the Shopify Partner Directory) or a trade body member list into one company row per listing, each carrying website, domain, tier, tags, and location for Clay-ready output. It runs the extraction on Apify, returning dataset rows for up to 20 directory URLs with optional deduping, detail enrichment, and a cost cap.

Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

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.

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

Classifies job titles into department and seniority using deterministic rules, and optionally verifies if a person is listed on their employer's website via the Mamba Labs Contact Classifier Apify actor.

Enables clients to interact with PipesHub data and functionality through MCP, including chat, search, record retrieval, directory browsing, sources, and agents.

MCP server that provides AI assistants with tools to understand, validate, generate, and transform CERIF 1.6 research information, including entity browsing, XML validation, document building, and migration from CERIF 1.5.

Enables AI assistants to interact with Hadoop Hue for executing SQL queries using Hive, SparkSQL, or Impala and managing HDFS files. It supports directory browsing, file transfers, and exporting query results to CSV through the Model Context Protocol.

MCP server for FormsList, a form-backend SaaS. Enables creating form endpoints, reading submissions, configuring auto-responses, and generating embed snippets via natural language.

A comprehensive MCP server that provides complete access to Qlik Sense applications and their detailed information for AI assistants and other MCP clients.

It gives AI agents a ranked, token-budgeted digest of what changed since their last cursor, with drill-down handles and cursor acknowledgement, read from a local database of file and SQL source changes. It enables agents to act on current business state without re-reading and diffing everything themselves.

Enables reading and writing Excel workbooks (.xlsx) through MCP. Supports listing sheets, tables, pivot tables, reading cell data, exporting to CSV/text/Markdown, and creating/modifying Excel files.

Enables AI agents and their users to ask business questions in plain language and receive governed metric values, breakdowns, share-of-total figures, and the exact parameterized SQL behind them, drawn from a single semantic model rather than ad-hoc SQL. It also lets clients inspect available metrics and their definitions, and preview optimized queries without executing them.

Enables programmatic interaction with Jupyter notebooks, allowing reading, editing, and executing cells via Claude.