Best HTTP Fetch MCP Servers

Reader is an AI data ingestion pipeline and web content parser designed to convert websites and documents into clean markdown for use with large language models. It functions as a headless browser content extractor and web-to-markdown converter, transforming URLs and PDF files into structured text formats while removing irrelevant web clutter. The system optimizes retrieval augmented generation by acting as a search optimizer that retrieves web results and applies re-ranking to improve context relevance. It further enhances content accessibility by using vision models to generate descriptive

This project is an MCP browser automation server that connects large language models to headless cloud browsers. It functions as an autonomous web workflow engine and an LLM web agent interface, enabling the translation of natural language instructions into browser actions and structured data retrieval. The system distinguishes itself through a managed headless browser cloud API that supports concurrent Chromium sessions with integrated stealth modes, CAPTCHA solving, and proxy traffic routing. It utilizes self-healing element selection to maintain automation resilience when page structures c

AnyCrawl is an AI-powered data extractor, automated web crawler, and headless browser orchestrator. It serves as a web content extraction API and a gateway that connects crawling and scraping tools to language models using a standardized API protocol. The project specializes in converting unstructured website content into structured JSON or markdown optimized for AI assistants. It utilizes language models and JSON schemas to pull specific information into validated formats and provides capabilities for AI page summarization and LLM-optimized content extraction. The system manages comprehensi

ACI is a tool-calling platform and centralized system for managing and executing external service operations and custom scripts for agentic workflows. It functions as a unified Model Context Protocol server that enables AI agents and IDEs to dynamically discover and execute diverse toolsets. The platform distinguishes itself through a natural language capability index and intent matching to search for available tools based on task requirements. It provides an external service authenticator and account linking via OAuth-based credential management to permit secure tool execution on behalf of u

Firecrawl is a web data extraction platform designed to convert unstructured web content into clean, LLM-ready formats like markdown or JSON. It functions as an autonomous web crawler and scraper, capable of mapping entire domains, performing recursive navigation, and executing complex data gathering tasks. By leveraging headless browser orchestration, the system handles dynamic, JavaScript-heavy pages to ensure comprehensive data capture. The platform distinguishes itself through its focus on agentic workflows, providing a programmatic interface that allows autonomous agents to perform live

Firecrawl is a headless browser automation tool and web crawling engine designed to extract structured data from the web. It functions as an API that transforms raw website content and documents into clean markdown and JSON formats to serve as context for large language models. The project distinguishes itself by using natural language prompts to translate human instructions into targeted data extraction tasks and browser actions. It can execute interactive page navigation, such as clicking and scrolling, and perform automated web research to retrieve structured data without manual interventi

FastMCP is a Python framework designed for building servers that expose functions, resources, and prompts to AI models using the Model Context Protocol. It simplifies the development process by automatically deriving tool metadata, input schemas, and documentation directly from Python function signatures and type hints. The framework provides a unified container for managing these components, allowing developers to build modular applications that integrate seamlessly with AI assistants. The project distinguishes itself through its support for interactive, server-defined user interface compone

Higress is an AI API gateway and cloud-native traffic manager that functions as a Kubernetes ingress controller. It provides a centralized system for routing, securing, and optimizing traffic directed toward large language models, AI agents, and microservice architectures. The project distinguishes itself through deep AI orchestration, including the ability to host and manage Model Context Protocol servers that transform REST APIs into tools for AI agents. It features specialized AI infrastructure for model request proxying, protocol translation across multiple providers, and semantic-based c

Atmosphere is a Java-based framework for building and coordinating AI agents. It provides a real-time transport layer for streaming data via WebSockets, SSE, gRPC, and WebTransport, alongside a multi-agent orchestration framework for managing agent fleets through sequential, parallel, and graph-based execution workflows. The project features a durable workflow engine that persists agent state as snapshots, allowing long-running tasks to survive system restarts and incorporate human-in-the-loop approvals. It also implements Model Context Protocol servers to expose tools, resources, and prompt

This project provides secure, containerized infrastructure designed for autonomous agents, remote code execution, and cloud development. It functions as a sandboxed environment where AI agents and external processes can execute code, run shell commands, and manage files while remaining isolated from the host system. The system distinguishes itself by implementing the Model Context Protocol, allowing it to act as a standardized tool server that exposes browser and filesystem capabilities to compatible clients. It further integrates headless browser automation, enabling programmatic web navigat

The Model Context Protocol is a standardized communication framework designed to connect language models to external data sources, functional tools, and interactive user interfaces. It provides a vendor-neutral interface layer that enables AI hosts to discover and execute capabilities across heterogeneous service environments, using a JSON-RPC based messaging standard to facilitate bidirectional communication between clients and servers. The protocol distinguishes itself through a robust capability-based handshake that negotiates feature sets during session initialization, ensuring compatibil

Eko is a framework for designing and deploying agentic workflows, featuring an LLM agent workflow orchestrator and a browser automation engine. It provides a server-side process manager for executing system-level operations and managing local files, alongside a human-in-the-loop agent controller for manual oversight and direction during automated decision processes. The system coordinates multi-agent collaboration through role-based partitioning and workflow orchestration, dividing complex tasks into distinct roles and managing execution handoffs. It integrates the Model Context Protocol to s