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.

Python 3.11+ License: MIT

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

Tool	Description	Output
`extract_file_overview`	File summary and identifiers	JSON
`extract_test_configuration`	Test setup and hardware config	JSON
`extract_yield_summary`	Pass/fail counts and yield %	JSON
`extract_facility_details`	Manufacturing facility info	JSON
`extract_program_metadata`	Test program version/config	JSON
`extract_test_parameters`	All test parameters with limits	JSON

Record Extraction Tools

Tool	Description	Filters	Output
`extract_pir_prr_records`	Part info and results	Site	JSON
`extract_ptr_records`	Parametric tests	Test name/number/suite, Site	JSON
`extract_ftr_records`	Functional tests	Test name/number/suite, Site	JSON
`extract_hbr_records`	Hardware bins	Site	JSON
`extract_sbr_records`	Software bins	Site	JSON
`extract_sdr_records`	Site descriptions	Site	JSON
`extract_mrr_record`	Master results	-	JSON

Analysis Tools

Tool	Description	Key Features	Output
`extract_test_parameter_summary`	Statistical summaries	Test suite filtering, Min/Max/Avg/StdDev	JSON
`extract_filtered_data`	Filtered data export	Test suite filtering, Multi-site	Excel (.xlsx)
`extract_test_time`	Test execution time	Site filtering, Statistics	CSV
`extract_per_unit_yield`	Per-unit bin data	3-column format (no PorF)	CSV

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

Operation	Target	Notes
Metadata extraction	<5 seconds	All 6 metadata tools
Record extraction	<10 seconds	For 1GB files
Filtered data	<30 seconds	With Excel generation
Test time analysis	<10 seconds	Multi-site support
Yield extraction	<5 seconds	10,000 units
Memory usage	<512MB	For 2GB files

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:

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Follow PEP8 and run code quality checks
Write tests for new functionality
Ensure all tests pass (pytest)
Commit your changes (git commit -m '[NewFeature] Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
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