"How to fetch or scrape data from a website for use in training an LLM" matching MCP servers:

A lightweight MCP server that fetches URLs and returns clean, readable markdown, enabling AI assistants to read any webpage with article extraction, caching, and security features.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

Lets AI agents see and control desktop applications through the accessibility layer, enabling clicking, typing, scrolling, dragging, and window/app management across macOS, Windows, and Linux entirely on the local machine.

Local MCP server for asynchronous coding-agent delegation, enabling Claude Code or Codex to delegate tasks to Cursor, Pi, Codex, or Claude Code and collect results later.

Manage a fleet of OPNsense firewalls from an AI agent, inside guardrails it can't drive around. MCP server for central management of OPNsense firewall fleets. 129 tools across devices, config sync, tasks, schedules, templates, backups and remote consoles - destructive actions confirmation-gated, MCP-issued tokens lifetime-bounded, backup and storage secrets excluded from the toolset entirely.

Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.

Open source MCP server specializing in easy, fast, and secure tools for Databases.

Enables LLMs to interact with embedded devices by reading and writing Segger RTT data through a J-Link debugger.

MCP server that integrates with VictoriaMetrics vmanomaly API to enable AI-assisted anomaly detection, model management, and configuration generation.

MCP server that will proxy to your gRPC backends via reflection or descriptors file.

An MCP front-end for AnB. The tool surface is "use-don't-reveal": no tool returns a plaintext secret. Reveal paths require a TTY the server doesn't have, so the no-reveal guarantee is structural, not prompt-based — it holds even against a prompt-injected agent. Runs as a dedicated, narrowly-scoped AnB identity; exec is default-deny (only allowlist rules tagged scope=mcp run); command output

MCP server for a self-hostable personal planner — exposes memo, todo, calendar event, and cross-resource full-text search tools so Claude, Cursor, or any MCP client can manage your schedule and notes in natural language.

A deterministic symbol oracle over a locally built index of the repository: whether a symbol exists, what a file declares, and what changed structurally since the last snapshot. It also ships a PreToolUse guard that stops an Edit/Write referencing a function, constant or type the repo does not declare, before the write lands rather than after the build fails. No LLM, no API keys, no network, no l

Decentralized Git with on-chain governance, bounties, and DAOs. Tools for repos, issues, PRs, labels, releases, bounties, and DAO proposals. Auto-wallet on first use, trust tiers, and approval mode for human-in-the-loop.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

Gives AI assistants real-time access to web data with the ability to scrape any website, bypass anti-bot systems, extract structured data, and capture screenshots through enterprise-grade infrastructure.

Connect Legacy Databases to AI Agents via Model Context Protocol. Open-source bridge for LLM data analysis.

A TypeScript server implementing the Model Context Protocol that provides secure code execution in isolated Docker containers, allowing LLM applications to safely run Python, Go, or JavaScript code snippets.

Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON

Enables AI video dubbing from any MCP-capable agent: upload a video or provide a URL, submit a dubbing job, poll progress, and download the finished MP4.