An open protocol layer for connecting and orchestrating heterogeneous scientific resources, building a global collaborative web of autonomous scientific Agents
- 📖 Table of Contents
- Overview
- ✨ Key Features
- 🏗️ Architecture Overview
- 🚀 Getting Started
- 🛠️ Tool Ecosystem
- 📊 Use Cases
- 🔬 SCP vs MCP
- 🌐 Related Links
- 📄 License
- Acknowledgments
SCP (Science Context Protocol) is an open-source standard protocol designed to accelerate scientific discovery by building a global web of autonomous scientific agents that connects heterogeneous resources such as software tools, models, datasets, workflow engines, and experimental instruments.
SCP provides:
- Protocol-level connectivity: Unified description and invocation of 1,600+ scientific resources (tools, models, instruments, etc.)
- Discovery-as-a-service: Manages the entire experiment lifecycle through a centralized SCP Hub and distributed SCP Servers
Developed by Shanghai Artificial Intelligence Laboratory, SCP aims to promote cross-institution, cross-platform scientific intelligence collaboration.
| Feature | Description |
|---|---|
| Unified Protocol Layer | JSON-based standardized interface for unified invocation of tools, models, and instruments |
| Intelligent Orchestration | SCP Hub supports automated planning, execution, and monitoring of multi-step workflows |
| Dry-Wet Experiment Integration | Seamless integration of computational tools and experimental devices |
| Multi-Agent Collaboration | Supports multiple AI agents working collaboratively in a unified context |
| Full Experiment Lifecycle Management | End-to-end traceability from registration, planning, execution to archiving |
| Security and Access Control | Fine-grained authentication and authorization mechanisms based on experiments |
SCP adopts a Hub-Spoke architecture:
SCP Client (User/Application)
↓
SCP Hub (Central Orchestrator)
↓
SCP Server (Edge Node) → Tools/Models/Instruments
- SCP Hub: Central orchestrator responsible for intent parsing, workflow generation, task scheduling, and permission management
- SCP Server: Edge nodes that interface with local resources (instruments, databases, models, etc.)
- SCP Client: User-facing interface for human researchers or AI scientists
# Clone the repository
git clone https://github.com/InternScience/scp.git
cd scp
# install
pip install mcp
# How to use
There are two ways to use SCP in your workflow:
## Option 1: Build & Manage Your Own
You can set up your own SCP Server and Hub using the provided code. This gives you full control over your deployment and management.
## Option 2: Use Intern-Discovery Platform (Recommended)
Visit the **[SCP Square](https://discovery.intern-ai.org.cn/org/ailab/workspace/iframe?url=https://scphub.intern-ai.org.cn/)** on our **[Intern-Discovery platform](https://discovery.intern-ai.org.cn/org/ailab/workspace/chat)**. We host a ready-to-use SCP Hub with a public registration interface. You can submit your own SCP Server to the square, and it will be integrated into the managed Hub, making it discoverable and accessible across the Intern-Discovery ecosystem.
Choose the approach that best fits your needs—whether you prefer full independence or a collaborative, managed environment.SCP has integrated 1,600+ tools, covering:
- Biology and Related Technologies (45.9%)
- Physics (21.1%)
- Chemistry (11.6%)
- Mechanics and Materials Science (8.7%)
- Mathematics (8.0%)
- Information Science and Computing Technology (4.6%)
| Use Case | Description |
|---|---|
| Automated Experimental Protocol Design | Generate executable experimental protocols from natural language objectives |
| Automated Reproduction from PDF Protocols | Extract experimental steps from PDFs and execute them automatically |
| AI-Driven Molecular Screening | Integrate QED scoring, ADMET prediction, and molecular docking |
| Dry-Wet Integrated Protein Engineering | Closed-loop workflow from sequence design to experimental validation |
For detailed case descriptions, refer to the Technical Report or User Cases.
| Feature | MCP | SCP |
|---|---|---|
| Protocol Standardization | General tool invocation | Structured full scientific experiment workflow |
| High-Throughput Experiment Support | No built-in experiment management | Supports batch experiments with context management |
| Multi-Agent Collaboration | Point-to-point communication | Centralized orchestration and task distribution |
| Wet-Lab Equipment Integration | Requires custom adapters | Standardized device drivers and interfaces |
- SCP Tool Plaza: Explore 1,600+ integrated tools
- Chinese SCP Documentation: Detailed usage guide
- Paper & Technical Report: SCP design and experimental details
- Community Discussions: Questions and discussions
This project is open source under the Apache License 2.0.
SCP is developed by Shanghai Artificial Intelligence Laboratory with support from the open-source community.
If you use SCP, please cite our technical report:
@article{jiang2025scp,
title={SCP: Accelerating Discovery with a Global Web of Autonomous Scientific Agents},
author={Jiang, Yankai and Lou, Wenjie and Wang, Lilong and Tang, Zhenyu and Feng, Shiyang and Lu, Jiaxuan and Sun, Haoran and Pan, Yaning and Gu, Shuang and Su, Haoyang and others},
journal={arXiv preprint arXiv:2512.24189},
year={2025}
}