"Using LLMs for Retrieving and Processing Web Content" matching MCP servers:

A TypeScript-based MCP server that enables AI assistants to execute HTTP requests with full control over methods, headers, and body content. It facilitates seamless interaction with web APIs and endpoints through a versatile tool that handles automatic JSON formatting and response truncation.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

Enables AI assistants to interact with the Post For Me API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Exposes read-only and write probes over a remote Streamable-HTTP /mcp endpoint so users can verify that ChatGPT Web discovers and calls remote tools, and test whether write actions actually execute on their plan. Real HWPX document editing is not yet supported; this P0 release only measures connectivity and read/write action boundaries.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

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.

Enables fetching content from any URL with support for different HTTP methods, custom headers, and request bodies. Designed to work with ChatGPT and other AI assistants for web scraping and API interactions.

Enables natural language interaction with FastAPI applications through Google's Gemini AI using MCP tools. Provides CRUD operations for user management and application health monitoring through conversational prompts.

Universal HTTP client tool for LLM agents. Enables Claude and other MCP-compatible agents to perform GET, POST, PUT, DELETE, and other HTTP requests to any URL, including localhost and internal network addresses.

MCP server for Akamai APIs. 198 tools covering Property Manager, Edge DNS, CPS, WAF, and reporting. Built with TypeScript, featuring modular architecture, comprehensive testing, and multi-account support. Make Akamai accessible to AI assistants.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

Free x402 endpoint checker plus paid report and metadata tools. Remote MCP server for agents. Written by AI named Nock, not a human.

This server enables interacting with the National Digital Health Mission's Health Information User (HIU) API, allowing agents to access and manage health information through the Multi-Agent Conversation Protocol.

Lets AI assistants safely explore a Matrix42 instance by discovering web services and the data model, running validated ASQL queries, searching the service desk, and previewing ticket actions — read-only by default and without exposing credentials.

Enables AI assistants to query API documentation from Eolink Apikit instances via the Eolink Open API, supporting listing projects, groups, searching APIs by keyword/path, and retrieving detailed API definitions.

Enables LLMs to make HTTP requests with OAuth2, session cookies, retry logic, and cURL command generation, while providing security features like SSRF protection and TLS enforcement.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Enables LLMs to make HTTP requests using structured cURL commands with support for multiple authentication methods, custom headers, and comprehensive request/response control.

Code Mode MCP server for the OVH API. Two tools (search + execute) give LLMs access to all OVH endpoints via sandboxed JavaScript.

Validates OpenAPI specs from files, inline content, or URLs, and generates prompts for agent developers based on the API analysis.