"search" matching MCP servers:

Provides fully local, privacy-preserving semantic search over file names and paths via MCP, using BGE embeddings for fuzzy matching and supporting incremental updates, watch mode, and a loopback-only HTTP server.

Enables AI assistants to perform offline semantic search over user-authorized code, documents, and images on macOS using EmbeddingGemma 2.

Enables AI assistants to run incremental SQLite FTS5 full-text search over explicitly configured local workspace roots, covering Markdown, code, PDF, DOCX, XLSX, CSV and HTML with BM25 ranking, Chinese bigrams, and phrase, prefix, path, type and date filters. Exposes search, safe root-confined reads with line/page/sheet locations, recent-file listing, and reindexing as MCP tools so assistants can locate and quote source content without network or account access.

A local-first MCP server that enables semantic search over PDF and DOCX documents using structure-aware parsing and vector storage. It allows users to query their local knowledge base through Claude Code without cloud dependencies or GPU requirements.

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

A Model Context Protocol server that enables keyword search within files, returning matching lines with line numbers.

Enables AI clients to search and read a local folder of notes, fetch public web pages as markdown with SSRF and robots.txt safeguards, and convert times between IANA timezones. It exposes these read-only capabilities as MCP tools over stdio or streamable HTTP.

Integrates Everything Search with Claude Code for lightning-fast file searching across entire drives, up to 400x faster than traditional methods.

Fast file search across Windows (Everything SDK), macOS (Spotlight/mdfind) and Linux (locate/plocate). Single search tool with platform-specific filters, sorting and an optional configurable tool name.

Enables fast file search on macOS using the native mdfind (Spotlight) command, with support for filtering, regex, sorting, and limiting results.

Integrates Everything file search with Claude Desktop, enabling instant Windows filesystem search via natural language queries.

Enables AI models to search, read, and analyze Excel files from your local file system with support for multiple worksheets, text search, and JSON data conversion.

A high-performance Model Context Protocol (MCP) server built for Windows. Leveraging the native Everything SDK, it provides AI models (like Claude, GPT, Gemini) with millisecond-speed file searching, statistical analysis, and disk usage insights.

Provides MCP tools to count, list, and read local documents in formats like PDF, DOCX, Excel, HTML, and TXT, enabling natural language-driven document statistics and content inspection via qwen_agent.

An MCP server that enables file system search and inspection, including directory listing, regex-based file name and content searches, and reading text, PDF, and DOCX files.

Enables AI assistants to search local files on Windows using the Everything search engine, supporting basic and complex file searches with filters like date, size, media type, and document type.

Enables intelligent file searching in local directories using natural language queries. Supports searching by file type, filename patterns, and content across multiple formats including PDF, Word, Excel, and text files with AI-powered relevance scoring.

Search local file contents recursively with keyword matching

Enables keyword searching within text files with configurable case sensitivity, returning matching lines with line numbers and occurrence counts.

Local MCP server that manages a job search using Markdown files, enabling skills tracking, gap analysis, and offer pipeline management via Claude.