STDF MCP Server

#STDF MCP Server

A Model Context Protocol (MCP) server that enables LLMs to efficiently access, analyze, and extract information from STDF-V4 (Standard Test Data Format) files used in semiconductor testing.

Features

17 Specialized Tools

Metadata Extraction (6 tools):

• extract_file_overview - Quick file assessment and key identifiers

• extract_test_configuration - Hardware setup and test environment

• extract_yield_summary - Test results analysis and yield calculation

• extract_facility_details - Manufacturing context and facility information

• extract_program_metadata - Test program and software version details

• extract_test_parameters - Comprehensive parameter listing with limits

Record Extraction (7 tools):

• extract_pir_prr_records - Part Information/Results Records

• extract_ptr_records - Parametric Test Records with filtering

• extract_ftr_records - Functional Test Records

• extract_hbr_records - Hardware Bin Records

• extract_sbr_records - Software Bin Records

• extract_sdr_records - Site Description Records

• extract_mrr_record - Master Results Record

Test Analysis (3 tools):

• extract_test_parameter_summary - Statistical summaries with test suite filtering

• extract_filtered_data - Excel extraction with multi-site support

• extract_test_time - Test execution time analysis with site filtering

Yield Analysis (1 tool):

• extract_per_unit_yield - Per-unit bin data extraction to CSV (PART_ID, HW Bin, SW Bin)

Key Capabilities

• STDF-V4 Format Support: Comprehensive support for STDF-V4 specification

• High Performance: Handles files up to 2GB with <512MB memory through streaming parser

• Multi-Site Support: Parallel test site data extraction and analysis

• Test Suite Filtering: Filter by test name, number, or suite with regex support

• CSV/Excel Export: Generate analysis-ready datasets

• Automatic Validation: Built-in file integrity validation

• TDD Development: Comprehensive test coverage with real STDF files

Quick Start

Installation

# Clone the repository
git clone https://github.com/your-org/stdf-mcp.git
cd stdf-mcp

# Install the package
pip install -e .

Running the MCP Server

# Start the MCP server
python -m stdf_mcp.simple_server

The server will start and listen for MCP protocol connections on stdin/stdout.

Configuration for Claude Desktop

Add to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "stdf": {
      "command": "python",
      "args": ["-m", "stdf_mcp.simple_server"],
      "cwd": "/path/to/stdf-mcp"
    }
  }
}

Replace /path/to/stdf-mcp with the actual path to your installation.

Usage Examples

Extract File Overview

# In Claude with MCP server connected
"Please extract the file overview from TestCases/example.stdf"

Returns: Lot ID, wafer count, device info, test dates, and file statistics.

Extract Yield Data

"Extract per-unit yield data from TestCases/production_test.stdf"

Generates CSV with columns: PART_ID, HW Bin, SW Bin

• Output location: TestCases/Output/production_test_YieldAnalysis_20251108_123045.csv

Filter Parametric Data

"Extract PTR records for test 'VDD_CURRENT' from TestCases/wafer_test.stdf"

Returns filtered parametric test results with statistics.

Test Time Analysis

"Extract test time analysis for site 1 from TestCases/multi_site.stdf"

Generates CSV with per-unit test execution times and summary statistics.

Tool Reference

Metadata Tools

Record Extraction Tools

Analysis Tools

Requirements

• Python: 3.11 or higher

• Dependencies:

  • mcp>=1.0.0 - Model Context Protocol SDK

  • numpy>=1.24.0 - Statistical calculations

  • matplotlib>=3.6.0 - Visualization (future)

  • openpyxl>=3.1.0 - Excel file generation

Development

Setup Development Environment

# Install with development dependencies
pip install -e ".[dev]"

# Install pre-commit hooks (optional)
pip install pre-commit
pre-commit install

Running Tests

# Run all tests
pytest

# Run with coverage report
pytest --cov=src/stdf_mcp --cov-report=html

# Run specific test categories
pytest -m unit          # Unit tests only
pytest -m integration   # Integration tests only
pytest -m contract      # Contract tests only

Code Quality

# Format code
black src/ tests/

# Type checking
mypy src/

# Linting
flake8 src/ tests/

# Run all quality checks
black src/ tests/ && flake8 src/ tests/ && mypy src/ && pytest

Project Structure

stdf-mcp/
├── src/stdf_mcp/          # Main package
│   ├── stdf/              # STDF parser and record definitions
│   ├── tools/             # MCP tool implementations
│   │   ├── metadata/      # Metadata extraction tools
│   │   ├── records/       # Record extraction tools
│   │   ├── test_summary/  # Test parameter summary
│   │   ├── filtered_data/ # Filtered data extraction
│   │   ├── test_time/     # Test time analysis
│   │   └── yield_analysis/# Yield data extraction
│   └── simple_server.py   # MCP server implementation
├── tests/                 # Test suite
│   ├── unit/             # Unit tests
│   ├── integration/      # Integration tests
│   └── contract/         # Contract tests
├── TestCases/            # Sample STDF files
│   └── Output/           # Generated outputs (gitignored)
├── specs/                # Feature specifications
├── pyproject.toml        # Package configuration
└── README.md             # This file

Performance Targets

Scope

Supported

• ✅ STDF-V4 format exclusively

• ✅ Package/final test data

• ✅ Files up to 2GB

• ✅ Streaming/chunked processing

• ✅ Multi-site test configurations

• ✅ Test suite filtering with regex

• ✅ CSV and Excel output formats

Not Supported

• ❌ STDF-V3 files (rejected with clear error)

• ❌ Wafer test data (package test only)

• ❌ Data retention between sessions

• ❌ Authentication/authorization

• ❌ Direct database access

Testing

The project uses a comprehensive TDD approach:

• Unit Tests: Core STDF-V4 parsing and data models (80%+ coverage)

• Integration Tests: End-to-end workflows with real STDF files

• Contract Tests: MCP tool API compliance verification

• TestCases Integration: Real STDF-V4 files from TestCases/ directory

• Output Standards: Results stored in TestCases/Output/ with timestamped naming

Troubleshooting

Common Issues

Issue: ModuleNotFoundError: No module named 'stdf_mcp'

• Solution: Install the package with pip install -e .

Issue: MCP server not appearing in Claude Desktop

• Solution: Check configuration file path and ensure cwd points to the correct directory

Issue: INVALID_STDF_FORMAT error

• Solution: Verify file is STDF-V4 format. STDF-V3 is not supported.

Issue: NO_PRR_RECORDS error for yield extraction

• Solution: File contains no Part Results Records. Verify it's a package test file.

Contributing

Contributions are welcome! Please:

1. Fork the repository

2. Create a feature branch (git checkout -b feature/amazing-feature)

3. Follow PEP8 and run code quality checks

4. Write tests for new functionality

5. Ensure all tests pass (pytest)

6. Commit your changes (git commit -m '[NewFeature] Add amazing feature')

7. Push to the branch (git push origin feature/amazing-feature)

8. Open a Pull Request

Commit Message Format

Use one of these prefixes:

• [NewFeature] - New functionality

• [Enhancement] - Improvements to existing features

• [BugFix] - Bug fixes

• [Document] - Documentation updates

• [WIP] - Work in progress

License

MIT License - see LICENSE file for details.

Acknowledgments

• STDF-V4 Specification: Teradyne Standard Test Data Format

• Model Context Protocol: Anthropic MCP

Support

For issues, questions, or contributions:

• Issues: GitHub Issues

• Discussions: GitHub Discussions

Version: 0.1.0 Status: Alpha Last Updated: 2025-11-08