"Techniques or Tools for Web Scraping" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Enables ChatGPT plugins and other MCP clients to fetch live web pages and documents as Markdown and to call HTTP APIs via self-hosted Cloudflare Workers.

A local MCP server that enables AI applications like Claude Desktop to securely access and work with Obsidian vaults, providing capabilities for reading notes, executing templates, and performing semantic searches.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

MCP server that exposes tools to route natural language queries to typed IDs, describe catalog entries, and list repository verification commands for the m-dev-tools organization.

MCP server that lets AI editors execute JavaScript, read console output, and simulate clicks/input on static web pages. Supports multiple browser pages and can be deployed remotely via HTTP transport.

Enables validating JSON/JSONC, getting/setting values with jq-like paths, pretty-printing or minifying, validating against Ajv JSON Schema, and diffing local files or inline strings without network calls.

Enables any MCP client to browse, triage, search, read, and drive pi coding agent sessions through Pi Web's HTTP API via 25 tools. Supports listing and filtering sessions, reading transcripts, flagging conversations awaiting input, sending messages and waiting for replies, inspecting project diffs, and forking, renaming, or deleting sessions over either stdio or Streamable HTTP.

Enables AI agents to pay per call for live package-safety and GitHub merge-readiness trust signals via the x402 protocol.

Enables agents to inspect localhost web applications through Chrome DevTools Protocol by listing Chrome targets, attaching to a page, capturing and querying network, console, navigation, and WebSocket events, and managing ephemeral sessions.

Provides computational tools for systematic reasoning, including boolean evaluation, date arithmetic, object counting, state tracking, and format validation, to enhance agent capabilities and eliminate calculation errors in reasoning tasks.

Provides AI-powered tools to apply UX/UI best practices, Nielsen's heuristics, cognitive biases, and Material-UI patterns to React components. Enables automated application of responsive design, Apple design patterns, and complete UX guidelines through natural language commands.

Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.

Review AI-generated HTML slides or reports in the browser, anchor comments to specific passages, and have the agent fix them via MCP, with tools for inspection, commenting, layout checking, and export to PDF/PPTX.

A local Model Context Protocol (MCP) server that exposes custom tools to Claude Desktop, enabling direct interaction with your local environment. It provides a framework for building and integrating custom TypeScript tools into the Claude interface.

Local MCP servers that give Claude Code access to other tools mid-session.

Enables users to select UI elements on localhost pages and send fix requests to MCP-compatible coding agents, which retrieve the captures and edit the code, with masking of sensitive values.

Enables AI agents to read any web page as clean Markdown and inspect its metadata, structure and technology stack, plus check redirects, TLS certificates, security headers, robots.txt, sitemaps, feeds, domains, SEO, broken links, email authentication (SPF/DMARC/DKIM) and SSO (SAML/OIDC). It also provides developer utilities such as cron, regex, color, Unicode and time-zone tools along with Hyperliquid perpetuals market data, all hosted remotely on Apify with pay-per-call pricing.

Transforms any API into an intelligent MCP agent in seconds, enabling natural language interaction with APIs through the Model Context Protocol.

Enables AI agents to perform common utility tasks through a streamable HTTP MCP endpoint, including JSON inspection, regex testing, cron parsing, hashing, base64 encoding/decoding, URL analysis, color conversion, text diffing, CSV parsing, JWT decode/verification, Markdown-to-HTML rendering, and UUID/token generation without API keys.