"Sublime Text" matching MCP servers:

An MCP server that extracts clean, structured Markdown content from web page URLs using the WebforAI library. It simplifies feeding web content into AI models by removing HTML noise and intelligently processing tables and links.

A Cloudflare Workers-based server that extracts clean, formatted text from web pages using WebforAI and makes it accessible to AI models through the Model Context Protocol.

Extracts clean, structured Markdown text from web pages using WebforAI, making web content easily accessible for AI model consumption through the Model Context Protocol.

Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.

An MCP server that finds relevant xkcd comics during conversation by semantically matching the context to comic titles, alt text, and transcripts.

MCP server that converts URLs into token-minimized clean text for LLMs, providing a receipt of token and cost savings.

Enables any MCP-aware LLM host to filter noisy text down to query-relevant sentences via a topic-conditioned relevancy classifier, reducing token spend before the model processes the full input.

A zero-cost, fully local MCP server that grounds AI assistants in verified web text, reducing hallucinations by ~80% by forcing answers only from fetched sources.

Rust-powered PDF toolkit over MCP: create, read, and analyze PDFs; extract text and entities for RAG; convert to Markdown; split/merge/rotate/reorder pages; manage form fields and annotations; encrypt documents. Runs locally via uvx oxidize-mcp.

Enables semantic search and retrieval over a locally supplied copy of Lemma's documentation, providing ranked excerpts and full-text chunk access via read-only MCP tools without calling live banking APIs.

Indexes local documents (PDF, Word, Markdown, text) into a SQLite database for AI agents to search and retrieve bounded, source-located passages. Runs fully locally with optional OCR, preserving privacy.

Enables agents to perform full-text search and read Hermes Agent documentation offline from a local cache, without scraping the site.

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.

A local MCP server that enables LLMs to securely search and read files within designated Google Drive folders. Supports Google Docs, Google Sheets, PDFs, and plain text with strict folder-scoping via service account authentication.

Extract YouTube transcripts for AI agents, RAG pipelines, and LLM workflows. Supports any YouTube URL. Returns clean text or timestamped segments. No API keys required.

Enables indexing local documents (PDF, Markdown, text, code) into a knowledge base and querying them via semantic search using local embeddings, all running privately on your machine.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

Verifiable document intelligence for AI agents. Extract text, tables, and structured data from PDFs and URLs. Summarize, answer questions, check claims, and translate — all with cited evidence. Store tamper-evident evidence bundles with cryptographic signatures and on-chain attestation via Base L2. Cross-document semantic search and Q&A across named collections. Pay per call with USDC

A read-only MCP server that lets you search current and historical facts from a time-indexed knowledge graph derived from a folder of Markdown/text documents, with verification against original sources. It exposes tools for status, fact search, history search, and revision lookup while keeping document insertion and modification to the CLI.

Access control for text-to-SQL agents. Before the model sees the schema, schemagate keeps only the tables and columns the caller may read, picks the few a question needs, and refuses hidden ones at query time. Postgres, Oracle, MySQL, SQL Server, SQLite. Quantum-safe signed audit log. Try it in your browser: https://ashishsinha1602.github.io/schemagate/