KI-Agenten
kuberna-labs
Build, deploy, and monetize autonomous agents across Web3.
★ 51 SterneMIT
Anleitung ansehen →Upsonic ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von Upsonic (Upsonic/Upsonic auf GitHub). Es hat 7.955 Sterne auf GitHub und 748 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 18. Juni 2026 auf GitHub aktualisiert.
Upsonic — build autonomous AI agents in Python, with prebuilt agents, custom tools, MCP and OCR built in.
Decide whether a prebuilt agent covers your task or you need a custom agent with your own tools, and which LLM it will use.
Clone Upsonic/Upsonic from GitHub (or use the install path in the run steps below) and skim its README for the parts relevant to your goal.
Install upsonic with uv or pip, adding the OCR extra if your agent must process documents.
Create a minimal autonomous agent from the quickstart, give it one tool and one real task, and check its output before adding complexity.
Build agents designed to work autonomously in Python, not just single prompt-response calls.
Start from the project's ready-made agents and customise them, instead of building every agent from zero.
Add your own tools to an agent so it can act on your systems and data.
Built-in OCR/document capabilities (via the upsonic[ocr] extra) for agents that must read documents.
Connects to Model Context Protocol tooling, so external MCP servers can extend your agents.
Documented IDE integration to develop and work with agents inside your editor workflow.
Get the source from the official GitHub repository for Upsonic.
git clone https://github.com/Upsonic/Upsonic.git
cd UpsonicInstall the package with uv as the README's quick start shows (pip works too).
uv pip install upsonicFollow the README/docs quickstart pattern to create an autonomous agent and run a task.
# In Python: create an Upsonic agent per the quickstart at docs.upsonic.ai, then run your task — see READMEUpsonic, through the Upsonic/Upsonic repository, with documentation at docs.upsonic.ai.
Yes — the project is open source under the MIT license as recorded for this listing. You can use, modify and distribute it under the MIT terms.
Agents need an LLM you configure — typically your own provider API key, billed by the provider; the framework itself is free and MIT licensed.
Upsonic focuses on building dependable single and autonomous agents in Python, with prebuilt agents, tools and OCR included. Broader multi-agent frameworks emphasise orchestrating many role-playing agents; Upsonic's pitch is a tighter, production-minded agent toolkit.
Clone the repository (or use the documented installer), follow the install and configure steps on this page, and run the smallest real task first — create a minimal autonomous agent from the quickstart, give it one tool and one real task, and check its output before adding complexity.
Build, deploy, and monetize autonomous agents across Web3.
Build production-ready AI agents in both Python and Typescript.
Chinese Java course: build AI agents with Spring AI, RAG, MCP, and tool calling.
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Mobile app automation and verification built for AI coding agents — CLI, MCP server, and Node API
Code, build and evaluate LLM agents with full MCP, Skills, ACP and A2A support.
Die anderen Projekte der Kategorie KI-Agenten mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls Upsonic nicht das Richtige ist.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Verwandte Projekte der Kategorie KI-Agenten im Katalog, die Upsonic bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Production-ready agentic RAG behind a clean REST API.
ZCode — Z.ai's AI coding workspace: desktop app, browser interface and terminal agent in one open-source harness
Osaurus — own your AI: a native macOS agent harness with any model, memory and fully offline execution.
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
All your agents and workspaces in one place — on every device you own.
A batteries-included browser API so agents can automate the web.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.