InternScience/protocol-generation-from-description

Laboratory Protocol Generation Workflow

Usage

1. MCP Server Definition

Use the same DrugSDAClient class pattern with Thoth-Plan server.

2. Protocol Generation from User Description

This workflow generates detailed laboratory protocols from natural language descriptions, useful for experimental planning and automation.

Workflow Steps:

1. Input User Description - Provide natural language description of desired protocol
2. Generate Detailed Protocol - AI generates step-by-step experimental procedure
3. Optional: Convert to Executable Format - Transform protocol to machine-readable JSON for automation

Implementation:

client = DrugSDAClient("https://scp.intern-ai.org.cn/api/v1/mcp/19/Thoth-Plan")
if not await client.connect():
    print("connection failed")
    return

## Step 1: Provide protocol description
user_prompt = """
I need a PCR protocol for amplifying a 500bp DNA fragment.
Use a standard Taq polymerase with the following conditions:
- Annealing temperature: 55°C
- Extension time: 30 seconds
- 30 cycles total
Include primer concentrations and buffer composition.
"""

## Step 2: Generate detailed protocol
result = await client.session.call_tool(
    "protocol_generation",
    arguments={
        "user_prompt": user_prompt
    }
)

protocol_text = client.parse_result(result)["protocol"]

print("Generated Protocol:")
print("=" * 80)
print(protocol_text)
print("=" * 80)

## Step 3 (Optional): Convert to executable JSON for lab automation
result = await client.session.call_tool(
    "generate_executable_json",
    arguments={
        "protocol": protocol_text
    }
)

executable_json = client.parse_result(result)["executable_json"]
print("\nExecutable JSON for lab automation:")
print(executable_json)

## Step 4 (Optional): Execute protocol via lab automation system
result = await client.session.call_tool(
    "execute_json",
    arguments={
        "executable_json": executable_json
    }
)

execution_info = client.parse_result(result)
print("\nExecution Info:")
print(execution_info)

await client.disconnect()

Tool Descriptions

Thoth-Plan Server:

• protocol_generation: Generate detailed laboratory protocol from description

  • Args: user_prompt (str) - Natural language description of desired protocol
  • Returns: protocol (str) - Detailed step-by-step protocol text

• generate_executable_json: Convert protocol text to machine-readable format

  • Args: protocol (str) - Protocol text
  • Returns: executable_json (str) - JSON format for Opentrons/lab automation

• execute_json: Execute protocol via connected lab automation systems

  • Args: executable_json (str) - Executable protocol JSON
  • Returns: Execution status and log

Input/Output

Input:

• user_prompt: Natural language description of desired experimental protocol
  • Can include: reagents, conditions, equipment, expected outcomes
  • Can reference standard protocols or specific parameters

Output:

• protocol: Detailed step-by-step protocol including:
  • Materials and reagents list
  • Equipment requirements
  • Detailed procedure steps
  • Safety considerations
  • Expected results
  • Troubleshooting tips

Example Protocol Types

The system can generate protocols for various laboratory procedures:

• Molecular Biology: PCR, cloning, gel electrophoresis, DNA extraction, transformation
• Protein Science: Protein purification, Western blot, ELISA, protein crystallization
• Cell Culture: Cell passage, transfection, differentiation, cryopreservation
• Biochemistry: Enzyme assays, metabolite extraction, chromatography
• Analytical: Spectroscopy, mass spectrometry sample prep, HPLC

Protocol Quality Guidelines

Generated protocols include:

• ✓ Precise volumes and concentrations
• ✓ Specific temperatures and times
• ✓ Safety warnings where applicable
• ✓ Quality control checkpoints
• ✓ Troubleshooting guidance

Integration with Lab Automation

The generated protocols can be converted to executable JSON format compatible with:

• Opentrons liquid handling robots
• Hamilton automated workstations
• Custom lab automation systems
• Electronic lab notebooks (ELNs)

Best Practices

For optimal protocol generation:

1. Be Specific: Include target specifications (e.g., "500bp fragment", "55°C annealing")
2. Mention Equipment: Specify if using particular instruments or kits
3. State Goals: Describe the experimental objective
4. Include Constraints: Note any limitations (time, budget, available reagents)
5. Reference Standards: Mention if following particular methods or publications

Example Good Prompts:

"Generate a Western blot protocol for detecting GAPDH (37 kDa) in HEK293 cell lysates using a standard semi-dry transfer system"

"I need a DNA extraction protocol from plant tissue (Arabidopsis leaves) optimized for downstream PCR. Yield target is 50 µg from 100mg tissue"

"Create a protein purification protocol for His-tagged recombinant protein from E. coli using IMAC chromatography. Starting culture volume is 500mL"

Limitations

• Generated protocols should be reviewed by qualified personnel before execution
• May require adjustment based on specific lab equipment and reagents
• Safety protocols should be verified against institutional guidelines
• Novel or untested procedures may need optimization