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SCP: Scientific Intelligence Context Protocol

An open protocol layer for connecting and orchestrating heterogeneous scientific resources, building a global collaborative web of autonomous scientific Agents

Official Site  Tool List  GitHub 


📖 Table of Contents


Overview

SCP (Scientific Intelligence 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.


✨ Key Features

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

🏗️ Architecture Overview

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

🚀 Getting Started

Installation and Deployment

# Clone the repository
git clone https://github.com/InternScience/scp.git
cd scp

# Start SCP Hub
docker-compose up hub

# Start an example SCP Server
docker-compose up server-example

🛠️ Tool Ecosystem

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%)

🔗 View Complete Tool List

📊 Use Cases

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 SCP Documentation.

🔬 SCP vs MCP

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

🌐 Related Links

📄 License

This project is open source under the Apache License 2.0.

🙏 Acknowledgments

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 Lu, Jiaxuan and Liu, Feng and Tan, Cheng and Lou, Wenjie and Sun, Haoran and Wei, Wangxu and Zhang, Bo and Wang, Lilong and Pan, Yaning and Tan, Pan and Wang, Xiaosong and Tang, Zhenyu and Gu, Shuang and Zhou, Dongzhan and Zhou, Bowen and Feng, Shiyang and Su, Haoyang and Ling, Fenghua and Bai, Lei},
  journal={arXiv preprint},
  year={2025}
}

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