"JSON Web Tokens" matching MCP servers:

Provides tools to fetch web content in HTML, JSON, text, or Markdown formats via MCP. Supports custom headers, length limits, and start index.

Enables fetching any public web page through managed proxies, with optional JavaScript rendering, returning markdown, text, HTML, or structured JSON.

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 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 AI agents to search the web, read and extract content from webpages, fetch JSON from REST APIs, and collect links while bypassing anti-bot protections.

Enables web search via DuckDuckGo and web content fetching through the Model Context Protocol, allowing AI assistants to search and retrieve web page content.

Enables bounded web research through DuckDuckGo search and retrieval of public HTTPS pages as readable text, Markdown, JSON, or XML, with optional excerpt matching and strict safety validation.

Converts any rendered web page into a complete, LLM-readable design specification—including block screenshots, distilled computed CSS, design tokens, responsive deltas, and alpha-channel-analyzed assets—so models can accurately reproduce the design.

Enables fetching, crawling, and browsing anti-bot protected web pages with real browser rendering, returning clean JSON or markdown, and solving captchas.

Enables converting webpages into structured JSON using CSS-selector schemas, with anti-bot handling and support for protected pages.

Enables AI agents and MCP clients to fetch web pages and distill them into clean, token-efficient markdown by stripping cookie banners, navigation bars, and ads. Runs with zero external dependencies over JSON-RPC stdio, delivering deterministic sub-millisecond results without LLM round-trips.

A local MCP server that gives Claude Code web search capabilities using DuckDuckGo, enabling discovery of URLs from natural language queries.

Amenbo is a Japanese-web-native MCP server for low-impact, token-efficient web collection, enabling agents to fetch, outline, and screenshot web pages while respecting robots.txt and optimizing for Japanese sites.

Provides web access tools (fetch, search, sitemap crawl) through String AI's API, automatically handling anti-bot bypass, CAPTCHA, and JavaScript rendering.

A web-fetch MCP server for LLM agents that fetches pages with an escalation ladder through different engines, raising FetchBlocked instead of returning blocked content.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

Structured web context infrastructure for AI agents. Extract reliable schema-guided JSON from websites using Claude-powered parsing, Browserless fallback rendering, and MCP-native workflows.

An open-source MCP server providing AI agents with neural web search via Exa and tiered web fetch (Exa, local browser, Firecrawl) as a drop-in replacement for built-in web tools, preserving provenance and guarding against SSRF.

Enables AI agents to check a list of websites by running an Apify Actor through one tool, returning per-site tech stack, on-page SEO issues and score, robots.txt rules for AI crawlers, sitemap, llms.txt presence, and an AI-readiness score. Supports local stdio operation with an Apify token for tool calls.

MCP server for SrezAI providing web search, page reading, screenshots, and schema-based extraction as native agent tools.