"curl" matching MCP servers:

Enables full curl functionality within the Model Context Protocol, allowing users to execute network requests with support for custom headers and host networking. It facilitates interaction with local and external APIs, including those using self-signed certificates, directly through Docker.

Turns any curl command into an MCP tool server by extracting placeholders and serving the request over stdio.

A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.

Furl folds repeated tool output into a hash-addressed marker, keeps the line that matters, and returns any original byte-exact the moment the agent asks for it. No summary. No guessing. Nothing thrown away.

MCP server that vets LLM-emitted shell commands BEFORE execution — detects rm -rf nested deep in chains, package-manager glob removal (apt remove 'nvidia'), dd/mkfs filesystem destruction, chmod 777 / chown -R privilege blast, network-exfil via curl | bash, chained shutdown/reboot, git destructive ops. 30 detection rules across 8 families. Sub-second, local, free, MCP-native.

An MCP server that enables AI assistants to diagnose network and service problems by walking a structured funnel of cURL timing metrics, identifying which hop is at fault, and providing targeted recommendations.

A coding agent toolkit that provides IDE-like semantic code retrieval and editing tools, enabling LLMs to efficiently navigate and modify codebases at the symbol level rather than working with entire files.

Enables extracting visible text and links from webpages for content analysis.

Enables AI models to fetch text content from URLs, extract links from web pages, and search the web using Brave Search with automatic content retrieval from top results. Provides comprehensive web scraping and search capabilities with robust error handling.

A Model Context Protocol (MCP) server that enables Claude or other LLMs to fetch content from URLs, supporting HTML, JSON, text, and images with configurable request parameters.

Enables sending files to LocalSend devices on the local network by scanning for devices and sending files using the LocalSend v2 protocol.

Provides a simple tool to shorten URLs using the CleanURI API, designed to run as a FastMCP server that can be integrated with agent or tool-based systems.

Enables AI agents to manage bookmarks (webpages, articles, videos) on behalf of users, including registration, categorization, tagging, and sharing.

Enables fetching visible text content and extracting all links from web pages through URL requests. Designed specifically for LM Studio integration to provide web scraping capabilities.

A Model Context Protocol (MCP) server that enables AI assistants to download files from URLs to the local filesystem.

Analyze YouTube, TikTok, and Instagram videos from URL. Extracts transcripts, generates AI insights, and pulls tutorial steps from any video link.

Enables AI agents to slice 3D models (STL files) headlessly using UltiMaker Cura's CuraEngine, returning ready-to-print G-code and estimated print time.

Enables autonomous web browsing and extraction by canonicalizing URLs, detecting anti-crawler traps such as circular paths and infinite pagination, pruning DOM content, mapping forms, converting tables to JSON, and evaluating agent trajectories.

Enables LLMs to manage tasks in a local SQLite database, with tools for creating, listing, updating, and deleting tasks.

Wraps the Remnawave panel API into 22 callable tools so AI assistants can manage VPN nodes, users, squads, config profiles, and hosts through natural language instead of manual curl requests. It supports listing, creating, enabling, disabling, restarting, and extending entities, along with traffic resets and node key generation, using credentials supplied via environment variables.