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

Enables stateless similarity search over pre-computed vector corpora using NMI and cosine fusion with entropy-calibrated weighting. Provides tools for ranking, scoring, outlier detection, and alpha calibration for AI agents.

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

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

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.

Share code context with LLMs via MCP or clipboard

Enables LLM clients to read, search, create, update, and delete notes in a self-hosted shared memory bank over MCP, using hybrid vector and full-text search with optional summarization.

MCP server that enables persistent, hybrid, local memory for LLM agents, with vector + BM25 search, knowledge graph, and policy-driven retention, providing token-budgeted context injection for AI assistants.

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.

This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

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.

CLI-first web and code search for agents, with MCP support for integration with IDEs like Cursor, VS Code, and Claude Code.

Enables an LLM to autonomously maintain a Markdown-based wiki with YAML frontmatter, using hybrid BM25 and local CPU vector search for fully offline retrieval without external APIs or databases.

Enables natural language query and ingestion of wiki knowledge bases built from documents, powered by Claude Agent SDK skills.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

A Model Context Protocol server that provides unified access to multiple LLM APIs including ChatGPT, Claude, and DeepSeek, allowing users to call different LLMs from MCP-compatible clients and combine their responses.

An MCP server providing RAG and CAG capabilities for querying and augmenting BambiSleep knowledge base data.