"Understanding Vector Search" matching MCP servers:

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

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

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

A production-style MCP server that lets Claude Desktop search your local documents using TF-IDF keyword search. No heavy frameworks, just plain Python and the official MCP SDK.

A sophisticated MCP server providing powerful file search capabilities including single file search, recursive directory search, and file information retrieval.

locidx

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.

Enables AI assistants to search indexed Windows drives for files and folders by name, path, type, size, or date, browse directories, and retrieve counts or total sizes in batched queries. It returns paginated results with optional metadata through a read-only local connection.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

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.

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.

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

Provides local hybrid search over files by combining semantic vector and full-text BM25 retrieval, with MCP stdio/HTTP support, OAuth 2.1 authentication, and tools for reading and converting documents to Markdown.

Provides integration with Everything Search Engine allowing powerful file search capabilities through the Model Context Protocol with advanced search options like regex, case sensitivity, and sorting.

Provides AI agents with access to file metadata, vector search, and workflow metrics. It enables operations such as file metadata retrieval and semantic search over file embeddings using pgvector.

Provides intelligent retrieval capabilities for local files by scanning directories, generating vector indexes, and enabling semantic search through RAG (Retrieval Augmented Generation) with incremental indexing support.

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.

Provides advanced document search and processing capabilities through vector stores, including PDF processing, semantic search, web search integration, and file operations. Enables users to create searchable document collections and retrieve relevant information using natural language queries.

Enables searching for files based on creation or modification timestamps within restricted root directories. It supports glob pattern matching, time range filtering, and pagination for efficient file discovery.

Lets MCP clients search, read, create, append, replace, move, and batch-update local Markdown notes safely, with conflict detection via SHA-256 and optional managed update blocks, without requiring a vector database.

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.

Offline AI-powered local file search MCP server for Windows. Searches inside document contents (Word, Excel, PDF, PowerPoint, HWP) using BM25 + dense vector hybrid search. 100% local, no cloud, no login, no telemetry.

Enables searching for a keyword within a text file using Model Context Protocol tools via standard input/output.

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.

Integrates with Everything Search Engine to provide lightning-fast file search capabilities across Windows systems using natural language queries and advanced filtering options through MCP-compatible applications.

Provides AI assistants with persistent memory through local ChromaDB vector storage, featuring automated file ingestion and batch processing for over 70 file types. It enables advanced vector search, EXIF metadata extraction for photos, and duplicate file detection across local directories.

A Model Context Protocol server providing file search and question tools for AI models. Enables keyword search in files with line numbers and integration with external chat services.