CHANGELOG.md

Changelog

All notable changes to the Predictive Maintenance MCP Server project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.7.1] - 2025-07-15

Added

• SSE & Streamable-HTTP transport — main() now accepts --transport sse|streamable-http (or env var MCP_TRANSPORT) via argparse CLI, enabling remote HTTPS deployment for Microsoft Copilot Studio and other networked MCP clients. --host / --port (or MCP_HOST / MCP_PORT) configure the listen address.
• Docker Compose + Caddy — New docker-compose.yml with mcp-server service (SSE by default) and commented-out Caddy reverse proxy for automatic Let's Encrypt HTTPS certificates. New Caddyfile template.
• HTTPS Deployment guide — New docs/DEPLOYMENT.md covering local SSE testing, Docker Compose + Caddy auto-TLS, nginx reverse proxy, Azure/cloud deployment, Copilot Studio connection, and CLI reference.

Changed

• Dockerfile rebuilt for SSE default — installs uvicorn, sets MCP_TRANSPORT=sse, MCP_HOST=0.0.0.0, EXPOSE 8000
• README updated: enterprise-ready features, Copilot Studio mention, deployment docs table, roadmap progress
• Version bumped to 0.7.1

[0.7.0] - 2025-07-14

Added

• FAISS vector search — search_documentation now uses FAISS + sentence-transformers for semantic retrieval when installed (pip install predictive-maintenance-mcp[vector-search]). Falls back to TF-IDF keyword search when not installed. Dual-backend DocumentIndex in src/rag.py.
• OCR for scanned PDFs — document_reader.extract_text_from_pdf() automatically falls back to Tesseract OCR for pages with empty/minimal text. Requires optional pytesseract + pdf2image + Poppler.
• DOCX diagnostic reports — New generate_diagnostic_report_docx MCP tool and save_diagnostic_report_docx() in report generator. Creates structured Word documents with statistics tables, FFT/envelope peaks, bearing frequencies, ISO evaluation, and diagnostic summary. Requires optional python-docx.
• New optional dependency groups in pyproject.toml: vector-search, ocr, docx. The full extra now includes all of them.
• Overlapping chunking — New chunk_text() helper in RAG module for character-level overlapping chunks alongside paragraph-aware chunking.

Changed

• search_documentation now reports active backend (faiss or tfidf) in response
• 27 MCP tools (was 26) — added generate_diagnostic_report_docx
• Version bumped to 0.7.0

[0.6.0] - 2025-07-08

Added

• RAG-based document search — New search_documentation MCP tool using TF-IDF indexing over machine manuals and bearing catalogs (src/rag.py)
• SpectralPeak model — Structured representation for individual FFT peaks (frequency, magnitude, dB, annotation)

Changed

• Compact FFT output — analyze_fft now returns top-20 peaks + RMS/stats instead of full frequency/magnitude arrays (~200 KB → ~2 KB per call), eliminating LLM context overflow
• Compact signal resource — read_signal_file returns metadata + statistics only (no raw samples), preventing large JSON payloads
• Server instructions updated with output-efficiency policy and RAG documentation guidance
• pypdf promoted from optional to required dependency

Fixed

• LLM "output too long" errors caused by full-array serialisation in FFTResult

[0.5.0] - 2025-02-16

Added

• Multi-format signal loading — load_signal_data() now supports CSV, TXT, NPY, MAT (MATLAB), WAV, and Parquet formats
• __main__.py — Server can now be run as python -m predictive_maintenance_mcp
• Ollama Guide added to documentation table in README

Changed

• Unified signal loading — All 16 pd.read_csv() call sites refactored to use load_signal_data(), enabling all tools to accept any supported format
• ML code deduplication — Extracted 4 helper functions (_resolve_sampling_rate, _segment_and_extract_features, _extract_features_from_files, _extract_and_transform_validation_features), reducing ~163 statements in train_anomaly_model
• ISO metadata consolidation — evaluate_iso_20816 now reads metadata file once instead of twice
• PyPDF2 → pypdf migration — Replaced deprecated PyPDF2 with pypdf in document_reader.py
• Pytest config consolidation — Merged pytest.ini into pyproject.toml ([tool.pytest.ini_options])
• Logging to stderr — Server logging now uses stderr to avoid polluting MCP stdio transport
• Report filenames — report_generator.py uses Path.stem for all filename sanitizations

Fixed

• Packaging — Corrected pyproject.toml package-dir mapping (src/ → predictive_maintenance_mcp)
• Metadata paths — get_metadata_path() now uses Path.stem to work with all signal extensions
• Plot output directories — Report generator creates output directories before writing files
• Flaky ML test — Fixed test_predict_anomalies instability with deterministic seed

[0.4.1] - 2026-02-15

Fixed

• Aligned __version__ in src/__init__.py and SERVER_VERSION in .env.example to 0.4.x (were still 0.3.4 after merge)
• Shortened server.json description to ≤100 characters (MCP Registry validation requirement)
• Added 0.4.x to supported versions table in SECURITY.md
• PyPI publish: v0.4.0 was uploaded with stale __init__ version; this release corrects it

[0.4.0] - 2026-02-15

Added

• Persona-Based Documentation System

  • New docs/QUICKSTART_ENGINEER.md — Zero-code guide for maintenance and reliability engineers
  • New docs/QUICKSTART_DEVELOPER.md — Architecture guide for AI/software developers with tutorial on creating new MCP tools
  • "Choose Your Path" section in README with two clear entry points

• "Our Mission" Section in README

  • Project vision and purpose integrated directly into the repository (previously only on external blog post)
  • Explains the "why" of MCP for industrial diagnostics

• Ecosystem Architecture Overview

  • Visual diagram explaining the MCP flow: User → LLM → MCP Server → Data
  • Explanation of MCP as "USB port for AI" — plug-and-play tool integration
  • Clarifies the Resource vs Tool pattern

• GitHub Issue Templates

  • Bug Report template with environment details
  • Feature Request template with impact assessment
  • Good First Issue template with effort estimates and mentorship links
  • Domain Validation template for engineers to provide expert feedback (no code required)
  • Pull Request template with standardized checklist
  • Issue template config with contact links to Discussions and guides

• Revamped CONTRIBUTING.md with Four Contribution Paths

  • Path 1: Domain Expert (no code required — validate results, provide datasets, review diagnostics)
  • Path 2: Software Developer (add tools, improve architecture, build Docker support)
  • Path 3: Technical Writer (tutorials, translations, case studies)
  • Path 4: Tester / QA (edge cases, cross-platform, ground truth validation)

• Actionable Roadmap

  • Roadmap items now link to GitHub Issues/Discussions
  • Priority-based table with Get Involved column
  • Docker image for zero-install setup added as high-priority item

Changed

• README.md completely restructured — Mission → Architecture → Choose Your Path → Content
  • Moved from purely technical README to narrative + technical hybrid
  • Added Documentation table linking all guides by audience
  • Consolidated support links (Issues, Discussions, Blog post) in dedicated section
• CONTRIBUTING.md rewritten — From generic PR guide to persona-based contribution manifesto
• Version bump from 0.3.2 to 0.4.0

[0.2.0] - 2025-11-11

Added

• Professional HTML Report Generation System

  • Interactive Plotly visualizations with modern, responsive design
  • generate_fft_report() - FFT spectrum analysis with peak detection
  • generate_envelope_report() - Bearing fault detection with frequency markers
  • generate_iso_report() - ISO 20816-3 compliance evaluation with zone charts
  • list_html_reports() - List all generated reports with metadata
  • get_report_info() - Extract metadata without loading full HTML

• Real Bearing Vibration Dataset

  • 20 production-quality signals from real machinery tests (train: 14, test: 6)
  • 3 healthy baselines, 7 inner race faults, 10 outer race faults
  • Sampling rates: 48.8-97.7 kHz, durations: 3-6 seconds (varies by signal)
  • Complete metadata with bearing frequencies (BPFO, BPFI, BSF, FTF)

• Advanced Diagnostics

  • Evidence-based bearing diagnostic workflow (diagnose_bearing)
  • Gear fault detection workflow (diagnose_gear)
  • ISO 20816-3 vibration severity assessment
  • Automatic acceleration→velocity conversion

• Machine Learning Tools

  • extract_features_from_signal() - 17+ statistical features
  • train_anomaly_model() - OneClassSVM/LocalOutlierFactor training
  • predict_anomalies() - Anomaly detection with confidence scores

• Comprehensive Test Suite

  • 80%+ test coverage
  • Real data validation tests
  • CI/CD pipeline with GitHub Actions
  • Automated code quality checks (pytest, flake8, mypy, black)

Changed

• Migrated from inline HTML artifacts to file-based reports
• Optimized signal processing algorithms for accuracy and performance
• Enhanced documentation with step-by-step tutorials
• Improved diagnostic accuracy with evidence-based workflows

Fixed

• Signal processing edge cases
• Peak detection accuracy
• ISO 20816-3 zone classification
• Metadata handling for various signal formats

[0.1.0] - 2025-11-01

Added

• Initial release of Predictive Maintenance MCP Server
• Core vibration analysis tools (FFT, envelope, statistics)
• Basic MCP server implementation with FastMCP
• Sample signal generation
• Initial documentation and examples

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Roadmap

Planned for v0.7.0

• 📦 Docker image for zero-install setup
• 📏 Customizable ISO report thresholds
• Multi-signal comparison tools
• Advanced trending and monitoring
• Additional diagnostic workflows (pumps, motors, gearboxes)
• Extended dataset with more fault types

Future Enhancements

• Real-time signal streaming support
• Cloud integration options
• Dashboard for multi-asset monitoring
• Mobile-friendly report viewing
• Integration with industrial IoT platforms
• Multimodal diagnostics: Combine vibration, temperature, acoustic data