Open-source framework for building AI-powered apps in JavaScript, Go, and Python, built and used in production by Google
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Updated
Nov 7, 2025 - TypeScript
Open-source framework for building AI-powered apps in JavaScript, Go, and Python, built and used in production by Google
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
The universal tool suite for vector database management. Manage Pinecone, Chroma, Qdrant, Weaviate and more vector databases with ease.
Add long-term memory to any AI in minutes. Self-hosted, open, and framework-free.
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
Enterprise-grade and API-first LLM workspace for unstructured documents, including data extraction, redaction, rights management, prompt playground, and more!
A Modern GUI Interface for Vector Database Management(Supports MCP integration)
A NodeJS RAG framework to easily work with LLMs and embeddings
Mercury - Train your own custom GPT. Chat with any file, or website.
Admin UI for Chroma embedding database built with Next.js
A dead-simple API to build LLM-powered apps
Memento MCP: A Knowledge Graph Memory System for LLMs
Example of building a chatbot with Langchain and Supabase Vector.
Visual and semantic vector similarity with Redis Stack, FastAPI, PyTorch and Huggingface.
The official TypeScript/Node client for the Pinecone vector database
Quickly and easily build AI website or application by using embeddings!
Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.
JavaScript/Typescript SDK for Qdrant Vector Database
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