https://github.com/upsonic/upsonic
The most reliable AI agent framework that supports MCP.
https://github.com/upsonic/upsonic
agent agent-framework claude computer-use llms mcp model-context-protocol openai rag reliability
Last synced: 18 days ago
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The most reliable AI agent framework that supports MCP.
- Host: GitHub
- URL: https://github.com/upsonic/upsonic
- Owner: Upsonic
- License: mit
- Created: 2024-05-26T16:23:38.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2025-05-01T17:11:21.000Z (about 1 year ago)
- Last Synced: 2025-05-01T17:49:53.512Z (about 1 year ago)
- Topics: agent, agent-framework, claude, computer-use, llms, mcp, model-context-protocol, openai, rag, reliability
- Language: Python
- Homepage: https://docs.upsonic.ai
- Size: 4.01 MB
- Stars: 7,398
- Watchers: 56
- Forks: 689
- Open Issues: 44
-
Metadata Files:
- Readme: README.md
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README
# Upsonic
**Build Autonomous AI Agents in Python**
[](https://badge.fury.io/py/upsonic)
[](LICENCE)
[](https://pypi.org/project/upsonic/)
[](https://github.com/Upsonic/Upsonic)
[](https://github.com/Upsonic/Upsonic/issues)
[](https://docs.upsonic.ai)
[](https://discord.gg/pmYDMSQHqY)
[Documentation](https://docs.upsonic.ai) • [Quickstart](https://docs.upsonic.ai/get-started/quickstart) • [Examples](https://docs.upsonic.ai/examples) • [Discord](https://discord.gg/pmYDMSQHqY)
---
## Overview
Upsonic is a Python framework for building autonomous agents like OpenClaw and Claude Cowork, as well as more traditional agent systems.
## Quick Start
### Installation
```bash
uv pip install upsonic
# pip install upsonic
```
### IDE Integration
Add Upsonic docs as a source in your coding tools:
**Cursor:** Settings → Indexing & Docs → Add `https://docs.upsonic.ai/llms-full.txt`
Also works with VSCode, Windsurf, and similar tools.
---
## Create Autonomous Agent
### Build Your Own
```python
from upsonic import AutonomousAgent, Task
agent = AutonomousAgent(
model="anthropic/claude-sonnet-4-5",
workspace="/path/to/logs"
)
task = Task("Analyze server logs and detect anomaly patterns")
agent.print_do(task)
```
All file and shell operations are restricted to `workspace`. Path traversal and dangerous commands are blocked.
### Use Our Prebuilt Ones
Prebuilt autonomous agents are ready-to-run agents built by the Upsonic community, each packaging a skill, system prompt, and first message so you can go from install to running in seconds. The collection is [open to contributions](https://github.com/Upsonic/Upsonic/tree/master/src/upsonic/prebuilt), bring your agent and open a PR.
Learn more: [Prebuilt Autonomous Agents](https://docs.upsonic.ai/concepts/prebuilt-autonomous-agents/overview)
> **Next steps:** Connect a [Sandbox Provider (E2B)](https://docs.upsonic.ai/concepts/autonomous-agent/overview) for isolated cloud execution environments.
---
## Create Traditional Agent
```python
from upsonic import Agent, Task
agent = Agent(model="anthropic/claude-sonnet-4-5", name="Stock Analyst Agent")
task = Task(description="Analyze the current market trends")
agent.print_do(task)
```
### Add Custom Tools
```python
from upsonic import Agent, Task
from upsonic.tools import tool
@tool
def sum_tool(a: float, b: float) -> float:
"""
Add two numbers together.
Args:
a: First number
b: Second number
Returns:
The sum of a and b
"""
return a + b
task = Task(
description="Calculate 15 + 27",
tools=[sum_tool]
)
agent = Agent(model="anthropic/claude-sonnet-4-5", name="Calculator Agent")
result = agent.print_do(task)
```
> **Next steps:** Integrate [MCP Tools](https://docs.upsonic.ai/concepts/tools/mcp-tools/overview) to connect your agents to thousands of external data sources and services.
---
## OCR and Document Processing
Upsonic provides a unified OCR interface with a layered pipeline: Layer 0 handles document preparation (PDF to image conversion, preprocessing), Layer 1 runs the OCR engine.
```bash
uv pip install "upsonic[ocr]"
```
```python
from upsonic.ocr import OCR
from upsonic.ocr.layer_1.engines import EasyOCREngine
engine = EasyOCREngine(languages=["en"])
ocr = OCR(layer_1_ocr_engine=engine)
text = ocr.get_text("invoice.pdf")
print(text)
```
Supported engines: EasyOCR, RapidOCR, Tesseract, PaddleOCR, DeepSeek OCR, DeepSeek via Ollama.
Learn more: [OCR Documentation](https://docs.upsonic.ai/concepts/ocr/overview)
---
## Check Our Videos
---
## Documentation and Resources
- **[Documentation](https://docs.upsonic.ai)** - Complete guides and API reference
- **[Quickstart Guide](https://docs.upsonic.ai/get-started/quickstart)** - Get started in 5 minutes
- **[Examples](https://docs.upsonic.ai/examples)** - Real-world examples and use cases
- **[API Reference](https://docs.upsonic.ai/reference)** - Detailed API documentation
## Community and Support
> **💬 [Join our Discord community!](https://discord.gg/pmYDMSQHqY)** — Ask questions, share what you're building, get help from the team, and connect with other developers using Upsonic.
- **[Discord](https://discord.gg/pmYDMSQHqY)** - Chat with the community and get real-time support
- **[Issue Tracker](https://github.com/Upsonic/Upsonic/issues)** - Report bugs and request features
- **[Changelog](https://docs.upsonic.ai/changelog)** - See what's new in each release
## License
Upsonic is released under the MIT License. See [LICENCE](LICENCE) for details.
## Contributing
We welcome contributions from the community! Please read our [Contributing Guide](CONTRIBUTING.md) and code of conduct before submitting pull requests.