"Understanding the text content of a webpage" matching MCP servers:

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

Lightweight content management system for websites, built for the AI era

An MCP server for codebase context that gives AI coding agents structural understanding through symbol graph, semantic search, blast radius, and convention detection tools.

An MCP (Model Context Protocol) server for managing Tailscale resources using the official Tailscale Go client library v2. This server provides complete coverage of the Tailscale API with enhanced, self-descriptive tools powered by OpenAPI documentation.

Enables AI assistants to structurally understand a Moodle installation and its plugins, so they can answer codebase questions and scaffold plugins that follow existing conventions. It scans Moodle sources and generates Markdown context files, indexes, and MCP tools/resources/prompts for querying, diagnosing, and maintaining that understanding.

A modern community hub with forum and knowledge base. Native MCP built-in, ready for the next era of internet culture.

Serves a folder as an MCP knowledge server: it indexes text, code, PDFs, office documents and audio or video, then answers search and ask calls with citations that name the file, the line range, the page or the time range. Runs fully local with Ollama by default; Mistral, OpenAI, Gemini and Anthropic are optional providers.

A high-performance, asynchronous MCP server that provides comprehensive Google search and web content scraping capabilities through the Firecrawl API, designed for LLMs to retrieve external information efficiently.

A personal content server that lets individuals publish content with cryptographic proof of authorship and explicit license terms, allowing AI agents to interact via the Model Context Protocol.

Neo4j MCP Canary is a fast-moving, experimental release of the Neo4j MCP server for customers who want to explore emerging capabilities before they are considered for the official server.

Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.

https://gopls-mcp.org/ MCP server for golang projects development: Expand AI Code Agent ability boundary to have a semantic understanding and determinisic information for golang projects.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

A Go-based MCP server that provides comprehensive access to the Serper Google Search API, including tools for images, news, maps, and scholar results. It also features a dedicated endpoint for scraping webpage content directly.

The implementation of Model Context Protocol (MCP) server for VictoriaLogs.

RootCause is a local-first MCP server that helps operators manage Kubernetes resources and identify the real root cause of failures through interoperable toolsets.

Converts URL content to Markdown, providing two tools: one for extracting main article content and one for converting the entire HTML.

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.

The implementation of Model Context Protocol (MCP) server for VictoriaMetrics

Gives AI coding agents a persistent memory that carries across sessions and projects, letting them save and search decisions, bug fixes, and discoveries through MCP tools. Each new session loads the recent memories of the current project so agents resume with the same context instead of re-explaining it.