"files and folders" matching MCP servers:

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.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

MCP server for Google's Gemini File Search (RAG). Manage file search stores, upload documents, and query with RAG through 12 tools.

Enables retrieval-augmented question answering over Obsidian vaults and document folders, with local embeddings, vector search, and cited source paths.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

A Model Context Protocol server that exposes Synapse Entities (Datasets, Projects, Folders, Files, Tables) with their annotations, enabling programmatic access to Synapse data resources through a RESTful API.

Serves any directory of Agent Skills (SKILL.md folders) over MCP, exposing skills/list, skills/get, and skill:// resources so clients can enumerate and retrieve each skill's frontmatter and files. Every returned file comes with a real SHA-256 digest, letting clients verify content rather than merely trust it.

A local hybrid-search MCP server that enables coding agents to query files and folders using natural language, returning relevant code chunks with exact source paths. Everything runs on-device with no API keys or network calls.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

Enables AI agents to perform fused hybrid search and reorganize documents, folders, and metadata in the SAGA document archive via MCP tools.

Enables LibreChat agents to manage per-user private files, persistent documentation, RAG indexing and semantic search, and publish files via secure opaque public links.

Turns Excel/CSV folders into a traceable, read-only AI knowledge layer; provides deterministic data queries, schema discovery, and evidence-backed search via MCP.

Local MCP server that indexes folders of documents into a hybrid vector + keyword search index for Claude Desktop, with support for PDFs, Office files, and images via OCR.

Enables local semantic and Japanese keyword search over Outlook Classic mail through MCP, including indexing connected mail folders and reading cached messages. It supports OpenAI-compatible embeddings, incremental sync, and metadata-filtered search via MCP tools.

Enables semantic code search across indexed code folders using vector embeddings, with support for multiple embedding providers and automatic file watching. Provides an admin UI and integrates with MCP clients for natural language code queries.

Enables agents to build self-hosted knowledge bases from document folders and search them via hybrid vector and keyword retrieval, with eight tools for listing, adding, deleting, and reindexing content.

Enables read-only semantic search over local folders of markdown, text, and optionally other document formats via a local vector store, without ever mutating the source files. It also watches each configured source for changes and auto-reindexes so search results stay fresh.

Enables reading and searching documents in allowlisted folders via LiteLLM and MCP tools, using COM for Office files to support IRM-protected content.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Provides tools for searching and reading local files, supporting metadata filters, PDF full-text keyword search, and sandboxed file access.