How do I use pyNastran MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@pyNastran MCP Server Analyze the mesh quality of wing.bdf and summarize any potential issues." That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

pyNastran MCP Server

Python 3.10+ License: MIT MCP

A Model Context Protocol (MCP) Server for pyNastran, built with FastMCP. Enables AI agents to interact with Nastran FEA models.

Features

🔧 BDF Tools: Read, write, and analyze Nastran input files
📊 OP2 Tools: Extract results from Nastran output files
🔍 Geometry Tools: Mesh quality checks and geometric analysis
📝 Analysis Tools: Automated report generation
🚀 FastMCP: Built with modern FastMCP framework
🌐 Multiple Transports: stdio, SSE, and streamable-http

Installation

pip install pynastran-mcp

Or install from source:

git clone https://github.com/Shaoqigit/pynastran-mcp.git
cd pynastran-mcp
pip install -e .

Quick Start

Stdio Transport (Default)

For MCP clients like Cherry Studio, Claude Desktop:

pynastran-mcp

SSE Transport

# Default: host=127.0.0.1, port=8080
pynastran-mcp --transport sse

# Custom host and port
pynastran-mcp --transport sse --host 0.0.0.0 --port 8080

Streamable HTTP Transport (Production)

# Default: host=127.0.0.1, port=8080
pynastran-mcp --transport streamable-http

# Custom host and port
pynastran-mcp --transport streamable-http --host 0.0.0.0 --port 8080

MCP Client Configuration

Cherry Studio / Cursor / Claude Desktop

Add to your MCP client configuration:

{
  "mcpServers": {
    "pynastran": {
      "command": "pynastran-mcp"
    }
  }
}

See CHERRY_STUDIO_TUTORIAL.md for detailed setup instructions.

Available Tools

BDF Tools

Tool	Description
`read_bdf`	Read BDF file and return model summary
`get_model_info`	Get detailed model information
`write_bdf`	Write model to new BDF file
`get_nodes`	Get node coordinates
`get_elements`	Get element connectivity
`get_materials`	Get material properties
`get_properties`	Get property definitions

OP2 Tools

Tool	Description
`read_op2`	Read OP2 result file
`get_result_cases`	List available result cases
`get_stress`	Extract stress results
`get_displacement`	Extract displacement results

Geometry Tools

Tool	Description
`check_mesh_quality`	Check mesh quality metrics
`get_model_bounds`	Get model bounding box

Analysis Tools

Tool	Description
`generate_report`	Generate comprehensive analysis report

Usage Examples

With AI Agents

Once configured, you can ask your AI assistant:

"Read the BDF file at /path/to/model.bdf and tell me about the mesh"
"Analyze the stress results from /path/to/results.op2"
"Check the mesh quality and suggest improvements"
"Generate a report for my Nastran model"

Programmatic Usage

from pynastran_mcp.tools.bdf_tools import BdfTools
from pynastran_mcp.tools.op2_tools import Op2Tools

async def analyze_model():
    # BDF Analysis
    bdf_tools = BdfTools()
    summary = await bdf_tools.read_bdf("wing.bdf")
    print(summary)
    
    # OP2 Results
    op2_tools = Op2Tools()
    stresses = await op2_tools.get_stress("results.op2", element_type="CQUAD4")
    print(stresses)

Project Structure

pynastran-mcp/
├── pynastran_mcp/
│   ├── __init__.py
│   ├── server.py          # FastMCP server with all tools
│   └── tools/
│       ├── __init__.py
│       ├── bdf_tools.py   # BDF file operations
│       ├── op2_tools.py   # OP2 result operations
│       ├── geometry_tools.py  # Mesh quality checks
│       └── analysis_tools.py  # Report generation
├── pyproject.toml
├── README.md
└── examples/
    └── example_usage.py

Requirements

Python 3.10+
pyNastran >= 1.4.0
mcp >= 1.0.0 (with FastMCP)

Development

# Setup
git clone https://github.com/Shaoqigit/pynastran-mcp.git
cd pynastran-mcp
pip install -e ".[dev]"

# Run tests
pytest

# Code formatting
black pynastran_mcp/

License

MIT License - see LICENSE file

Acknowledgments

pyNastran - The underlying Nastran interface library
MCP Python SDK - FastMCP framework

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add some amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

Please make sure to update tests as appropriate and follow the existing code style.

pyNastran - The underlying Nastran interface library
MCP Python SDK - FastMCP framework

pyNastran MCP Server

pyNastran MCP Server

Features

Installation

Quick Start

Stdio Transport (Default)

SSE Transport

Streamable HTTP Transport (Production)

MCP Client Configuration

Cherry Studio / Cursor / Claude Desktop

Available Tools

BDF Tools

OP2 Tools

Geometry Tools

Analysis Tools

Usage Examples

With AI Agents

Programmatic Usage

Project Structure

Requirements

Development

License

Acknowledgments

Contributing

Resources

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