"JSON File Upload, Data Vectorization, and LLM Similarity Search" matching MCP servers:

Search local file contents recursively with keyword matching

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.

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

Enables natural language search and discovery of open-access scientific datasets through the EOSC Data Commons OpenSearch service. Provides tools to search datasets and retrieve file metadata using LLM-assisted queries.

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 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.

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

Enables semantic search over personal files using natural language, with optional AI summarization, all running locally.

A Model Context Protocol server for querying large JSON files using JSONPath expressions, enabling LLMs to efficiently search and extract information from large JSON data.

Provides read-only MCP tools to query the ETIM classification model, enabling AI agents to search classes, retrieve feature/unit definitions, and look up ETIM codes.

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

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.

Provides web search and page fetching capabilities using Ollama's API.

MCP server for grounded, cited AI: answers questions from live web sources, verifies claims, fact-checks documents, searches and reads URLs, summarises, classifies, and extracts fields, with usage tracking and status.

Enables efficient navigation and search of large JSON files (>10MB) through intelligent path exploration and fuzzy search capabilities, designed to save tokens by avoiding loading entire files into context.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

Enables LLM agents to securely explore, read, search, and analyze text-based files within a sandboxed environment.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Give your AI assistant real-time LLM/VLM knowledge. Pricing, benchmarks, and recommendations — updated every hour, not every training cycle.

Monitors brand mentions, citations, sentiment, competitor share of voice, and GEO performance across AI search engines.