"Markdown" matching MCP servers:

Converts documents (PDF, DOCX, XLSX, EPUB, etc.) to clean, structured Markdown, and retrieves document info, for use with AI agents.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

MCP server that parses web pages into clean markdown via Crawl4AI's HTTP API, exposing parse_page and health-check tools with configurable proxy and timeout.

Address Markdown and GEML documents by block instead of by line: list, get, set, add, delete, rename, revert, find and check one block, with every write re-parsed and refused if it would brea

Local-first memory for coding agents. Discovers the memory, instructions, and rules Claude Code, Codex, and Cursor already wrote on your machine, combines them into one canonical Markdown tree, and serves grounded, cited recall through tools like ask_memory and canonical_memory.

Real-time Amazon Sponsored Products (SP) ad placements, keyword tracking, and comprehensive review data for AI Agents. Enables LLMs to autonomously conduct competitor ad audits, consumer sentiment analysis (VOC), and product optimization.

Provides a persistent memory and governance layer that allows AI coding agents to query documented architecture rules and validate code against team standards. It enables agents to verify compliance across categories like security and testing before suggesting changes to ensure consistency across development sessions.

On-premises knowledge retrieval over the Markdown, text, PDF, Word and Excel files an organization keeps, with the rules you set enforced before anything is retrieved. Agents connect over MCP, get cited passages, and read from it and never write to it.

Enables MCP-aware AI agents to scrape web pages into markdown, screenshots, metadata, and links, map sites, run asynchronous scrape jobs, and check usage, with EU-hosted, GDPR-aligned processing.

Web tools for AI agents. Search the web for full page content, fetch URLs as clean markdown including PDFs, extract structured data from a page with a prompt, and run multi-source deep research that returns a cited report.

A production-ready Model Context Protocol server that enables language models to leverage AI-powered web scraping capabilities, offering tools for transforming webpages to markdown, extracting structured data, and executing AI-powered web searches.

Enables LLM clients to run Brave LLM Context web searches and fetch readable markdown extracts from URLs, including specialized site extraction, PDF text, raw mode, and pagination.

MCP server for Octen Extract that turns any URL into clean, LLM-ready markdown, with highlights and classification. Works with Claude, Cursor, VS Code, and other MCP clients.

Read any public web page as a clean AIDocument: Markdown plus title, description, and structure, with navigation and boilerplate stripped. Reads resolve through Lyrenth's shared cache, so it is far fewer tokens than raw HTML and origin-friendly.

Pay-per-call x402 APIs for AI agents: DeFi token safety (honeypot/tax simulation, A-F grade), EVM chain data, web access (markdown/screenshot/PDF), speech-to-text. USDC on Base, no account, no API key

Enables AI agents to scrape, crawl, and map websites into LLM-ready markdown via the Metalift API

Enables AI agents to convert files, render web pages to markdown/PDF/screenshots, search the live web, extract structured data, ingest RAG-ready chunks, and monitor pages for changes through a single API key.

MCP server that enables AI agents to fetch web content as clean, structured Markdown via NanoParse's hosted API, using x402 micropayments in USDC on Base.

Local-first MCP server that captures web URLs (X, Reddit, YouTube, Wikipedia, articles) as typed data + Markdown into a self-hosted capture/store/recall substrate, with offline semantic recall. Six tools over a local khiipd daemon; run khiipd serve first.