"让AI大模型读取和分析本地文件（Word/Excel/PDF/Markdown/代码等）的方法" matching MCP servers:

Enables AI to search, retrieve, list notes, and get backlinks from a published Markdown vault (Obsidian) via GitHub Pages.

Provides structured, addressable access to a local markdown vault with heading-anchored fragments, BM25 search, and stable IDs for verifiable retrieval.

Enables querying Excel and CSV files using SQL via natural language, allowing AI assistants to analyze data without manual SQL writing.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.

A generic Markdown vault MCP server with FTS5 full-text search, semantic vector search, frontmatter-aware indexing, incremental reindexing, and non-markdown attachment support that exposes search, read, write, and edit tools.

A Model Context Protocol server that enables AI agents to read, search, and extract content from PDF files.

Headless semantic MCP server for Obsidian, Logseq, Dendron, Foam, and any markdown folder. Features built-in hybrid semantic search, surgical AST editing, template scaffolding, zero-config local embeddings, and workflow tracking.

Enables semantic search of the KJV Bible and personal knowledge graph for scripture study, notes, prayers, and memory verses, all running locally with no cloud dependencies.

The local PDF workflow for Claude Desktop and MCP hosts: fill, sign, merge, split, extract, and analyze PDFs without sending files to a web app.

Enables querying Markdown files in knowledge bases (like Obsidian vaults) by front matter metadata, filtering notes by tags, recency, and folders to surface relevant content based on created/updated dates.

Provides semantic search over markdown documentation using RAG, allowing natural language queries and integration with MCP clients.

Enables managing and searching markdown notes with semantic search, question answering, and note generation, and provides an MCP server for GitHub Copilot integration.

Fetches web pages and converts them to clean, readable markdown format by extracting main content while removing navigation, ads, and other non-essential elements to minimize token usage.

An MCP server for local PDF inspection that classifies, searches, extracts text and tables without uploading documents or relying on OCR, surfacing reliability warnings for garbled or scanned content.

MCP server for full-text search across PDF document collections with offline indexing, ranked results, snippets, and page rendering.

Enables a persistent local library for mathematical PDFs with cached LaTeX extraction, full-text search in English and Greek, and page/image retrieval over MCP.

An MCP (Model Context Protocol) server that provides structured access to ISO 32000 (PDF) specification documents. Enables LLMs to navigate, search, and analyze PDF specifications through well-defined tools.

Enables AI agents to efficiently process large local and online PDFs through selective extraction of text, images, and metadata. It provides tools for content search and document outline navigation to optimize context window usage.

A local RAG MCP server for PDF development experience, enabling document ingestion, semantic search, and Q\&A with source citations using TF-IDF and cosine similarity.

Enables assistants to search a Zotero library, retrieve metadata and PDF text, and view PDF pages as rendered images so figures and layouts are visible.