Áudio
cheetah
On-device streaming speech-to-text engine for real-time apps.
★ 670 estrelasApache-2.0
Ver o guia →codealive-mcp é um projeto de RAG e conhecimento de código aberto de CodeAlive-AI (CodeAlive-AI/codealive-mcp no GitHub). Tem 90 estrelas no GitHub e 9 forks, é publicado sob a licença MIT e foi atualizado pela última vez no GitHub em 24 de setembro de 2026.
Codealive-mcp, in Python — built for context engine for large codebases, exposed throug...
Fetch the source code onto your machine.
Set up the Python environment the project needs.
Copy the sample config or env file and adjust it.
Start the app from the source directory.
Built around claude code for a focused workflow.
Built around cursor for a focused workflow.
Built around graphrag for a focused workflow.
Built around large codebase for a focused workflow.
Inspect, fork, and modify every line of the code.
Run it on your own machine — no account lock-in.
Get the source on your machine.
git clone https://github.com/CodeAlive-AI/codealive-mcp.gitSet up Python dependencies.
cd codealive-mcp && pip install -r requirements.txtLaunch the application.
cd codealive-mcp && python main.pyIt context engine for large codebases, exposed through MCP. Gives AI coding agents precise repository context; benchmarked at frontier-agent quality with ~25x lower model cost and 45% fewer tokens with semantic search, giving you a working starting point you can run and adapt.
Yes — the code is open-source, so you can use and modify it without a license fee.
Clone the GitHub repository and follow the README; the typical flow is install dependencies, configure, and run.
It is primarily written in Python, so you will need that toolchain to build or extend it.
The GitHub repository is the hub: open issues for bugs and check the README and discussions for guidance.
On-device streaming speech-to-text engine for real-time apps.
Open source AI resume builder, Next.js 15, React 19, Tailwind CSS
Feature-rich WhatsApp bot built on Baileys' multi-device protocol.
A blazing-fast vector index in Rust, built on TurboQuant - with Python bindings
Incremental engine that keeps RAG indexes and agent context fresh by processing only the delta.
A self-hostable markdown team wiki with a built-in MCP server.
Os outros projetos de RAG e conhecimento com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se codealive-mcp não for o ideal para você.
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or…
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context…
Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
Projetos de RAG e conhecimento próximos no catálogo, os mais próximos em estrelas de codealive-mcp: continue explorando dos dois lados dele.
AST-powered code intelligence engine — graph database plus hybrid semantic search across 62 languages, zero LLM dependency.
AI agent operating system for Blender 5.2 — bpy knowledge base, execution contract, 3D-print production gate.
Self-hosted rag & knowledge: cometchat docs search + implementation bundles: add cha.
Run rag-template locally: template for ai chatbots & document management using re.
Rag.computer — self-hostable rag platform - document ingestion, embedd, open-source.
Libratory, in TypeScript — built for your free book and audiobook laboratory. turn the...
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.