v2.1.4 - MCP Registry Support

What's Changed

Added

• MCP Registry Support: Added server.json and mcp-name metadata for MCP Registry publication
• Ready for publication to https://registry.modelcontextprotocol.io

Next Step

After PyPI publishes, run in Empathy project:

/tmp/mcp-registry/bin/mcp-publisher publish

Full Changelog: v2.1.3...v2.1.4

v2.1.3 - Dependency Updates

What's Changed

Updated

• Upgraded Codecov action to v5 with verbose output for better CI integration
• Updated MCP dependencies for compatibility:
  • pydantic 2.5.3 → 2.12.5
  • httpx 0.26.0 → 0.28.1
  • pydantic-settings 2.1.0 → 2.12.0
  • python-multipart 0.0.6 → 0.0.20
  • uvicorn 0.27.0 → 0.38.0

Full Changelog: v2.1.2...v2.1.3

v2.1.2 - Smart AI Memory Branding

What's Changed

Rebranding

• Updated all documentation and links from Deep Study AI to Smart AI Memory
• Updated GitHub repository URLs to Smart-AI-Memory organization
• Updated copyright in LICENSE to Smart AI Memory
• Updated website references to smartaimemory.com

Full Changelog: v2.1.1...v2.1.2

v2.1.1 - Enterprise Production Ready

What's New in v2.1.1

Enterprise Security Documentation

• SOC 2 Type II compliance checklist with trust criteria mapping
• HIPAA readiness guide for healthcare deployments
• Security architecture documentation (defense-in-depth)
• Data residency guide - complete data location control
• Air-gapped installation instructions for offline environments

Code Quality Improvements

• Test coverage increased to 86% (435 tests passing)
• Focused core - wizards moved to separate domain archives
• Version sync fixed across all files

MemDocs Core Mission

MemDocs is now focused on its core competencies:

• Git-native memory storage for AI assistants
• Cross-conversation LLM memory (Claude Code, etc.)
• Enterprise audit-ready security (PHI/PII redaction)
• MCP server for Claude Desktop integration

Documentation

• New docs/security/ directory with compliance guides
• New docs/enterprise/ directory with deployment guides
• Comprehensive API reference documentation

Installation

pip install memdocs==2.1.1

Full Changelog

See CHANGELOG.md

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🤖 Generated with Claude Code

v2.1.0 - Enterprise Production Ready

What's New in v2.1.0

Enterprise Security Documentation

• SOC 2 Type II compliance checklist with trust criteria mapping
• HIPAA readiness guide for healthcare deployments
• Security architecture documentation (defense-in-depth)
• Data residency guide - complete data location control
• Air-gapped installation instructions for offline environments

Code Quality Improvements

• Test coverage increased to 86% (435 tests passing)
• Focused core - wizards moved to separate domain archives
• Version sync fixed across all files

MemDocs Core Mission

MemDocs is now focused on its core competencies:

• Git-native memory storage for AI assistants
• Cross-conversation LLM memory (Claude Code, etc.)
• Enterprise audit-ready security (PHI/PII redaction)
• MCP server for Claude Desktop integration

Documentation

• New docs/security/ directory with compliance guides
• New docs/enterprise/ directory with deployment guides
• Comprehensive API reference documentation

Installation

pip install memdocs==2.1.0

Full Changelog

See CHANGELOG.md

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🤖 Generated with Claude Code

v2.0.15: Enhanced Documentation & Git-Committed Memory

🎉 Release v2.0.15

✨ New Features

• Enhanced Module Docstrings: Added comprehensive documentation to 6 core components

  • MCP Server: Clarified flagship Claude Desktop integration
  • Extract: Documented multi-language symbol extraction
  • Embeddings: Highlighted zero-cost ($0) local operation
  • Search: Detailed FAISS-based offline vector search
  • Summarize: Described Claude Sonnet 4.5 powered documentation
  • Policy: Explained intelligent scope escalation logic

• Dogfooding: Committed .memdocs/ directory to git

  • MemDocs now documents itself with production-quality memory
  • 54 symbols documented and searchable
  • 124KB of git-committed AI memory
  • Demonstrates best practices for git-native documentation

📊 Memory Statistics

• Symbols: 54 documented classes and functions
• Embeddings: 20 semantic search chunks indexed
• Coverage: 100% of core modules documented
• FAISS Index: 29KB for fast similarity search
• Cursor Integration: .cursorrules file (8KB) exported

🔧 Improvements

• Updated .gitignore to enable committing .memdocs/
• Production-ready MCP server documentation
• Accurate commit-based documentation generation

📚 Full Changelog

• release: Bump version to 2.0.15 (b25b20c)
• feat: Add comprehensive MemDocs memory for core modules (a8e2410)
• docs: Enhance module docstrings for core engine components (1b02247)

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Install: pip install memdocs==2.0.15
Upgrade: pip install --upgrade memdocs

🤖 Generated with Claude Code

Version 2.0.14

Updated contact information

MemDocs v2.0.0-beta - Production-Grade Quality, 84.6% Coverage

MemDocs v2.0.0-beta 🧠

Production-Grade Quality, Beta for User Validation

What is MemDocs?

MemDocs is a git-native memory management system that gives AI assistants persistent, project-specific memory. It generates structured, machine-readable documentation that lives in your repository—no cloud services, no recurring costs, just local/git-based storage.

📊 Why Beta? Production Quality, Early Validation

Code Quality Assessment (Third-Party Standards):

• ✅ PyPI Production Criteria: 83% (5/6 requirements met)
• ✅ OpenSSF Best Practices: 90% (60/67 passing badge criteria met)
• ✅ Test Coverage: 84.6% (334 tests passing) 🎯 Exceeds 80% production threshold
• ✅ Security: All critical vulnerabilities resolved
• ✅ Python Support: Tested on 3.10, 3.11, 3.12

Why Beta?
We're releasing as beta not due to code quality concerns, but because we need production user validation before committing to full API stability. The codebase is production-ready—we're looking for early adopters to help validate real-world usage patterns.

Translation: The code is solid. We need you to kick the tires.

✨ Key Features

• 🧠 Persistent Memory: AI assistants remember your project across sessions
• 👥 Team Sharing: Memory committed to git and shared with your team
• 💰 Zero Cost: No vector databases, no embeddings API, no subscriptions
• ⚡ Works Offline: No cloud dependencies for retrieval
• 🤝 Empathy Framework: Integration available via empathy package
• 🔒 Privacy First: Optional PHI/PII detection and redaction
• 🎯 Claude Sonnet 4.5: Latest and most powerful Claude model

🚀 Quick Start

# Install
pip install memdocs==2.0.0b0

# Set your API key
export ANTHROPIC_API_KEY="your-key-here"

# Initialize in your project
cd your-project
memdocs init

# Review a file or directory
memdocs review --path src/

# Query your project memory
memdocs query "how does authentication work?"

# View statistics
memdocs stats

📦 What's New in 2.0

Major Enhancements

• Rebranding: DocInt → MemDocs (new name, same powerful memory)
• Claude Sonnet 4.5: Updated to latest, most capable model
• Modular CLI: Refactored 928-line monolith into clean command structure
• Security Hardening: Path traversal protection, input sanitization, API key handling
• Complete Type Hints: 100% type coverage for better IDE support
• MCP Server: Model Context Protocol support for Claude Desktop integration

Recent Improvements

• ✅ Wizard Exclusion: Empathy-specific code moved to empathy package (cleaner separation)
• ✅ Improved Coverage: 84.6% (was 79% with wizards)
• ✅ Accurate token counting with tiktoken
• ✅ Dependency parsing for Python & JavaScript projects
• ✅ Configurable max_tokens for Claude API
• ✅ Python 3.10+ compatibility (tomli backport)
• ✅ Lazy numpy imports (core features work without embeddings)

Infrastructure

• ✅ GitHub Actions CI/CD (linting, tests, type checking)
• ✅ Pre-commit hooks configured
• ✅ Security policy (SECURITY.md)
• ✅ Contributing guidelines
• ✅ Code of Conduct

🎯 Quality Metrics

Metric	Target	Actual	Status
Test Coverage	80%	84.6%	✅ Exceeds
Security Issues	0	0	✅ Pass
Python Versions	3.10+	3.10-3.12	✅ Pass
Documentation	Complete	Complete	✅ Pass
CI/CD	Configured	Active	✅ Pass
Linting	Clean	16 minor	⚠️ Acceptable

📦 Package Information

Lean & Focused: Wizards/integrations excluded from core package

• Core MemDocs functionality only
• Empathy integration available via: pip install empathy
• Smaller package size, clearer separation of concerns

🐛 Known Limitations

• CLI integration tests: Some command modules lack integration tests
• Tree-sitter: TypeScript/JavaScript extraction planned but not yet implemented
• Linting: 16 minor style warnings (non-blocking)

These are documented and tracked, none are blocking for basic usage.

📚 Resources

• GitHub: https://github.com/Smart-AI-Memory/memdocs
• Issues: https://github.com/Smart-AI-Memory/memdocs/issues
• Discussions: https://github.com/Smart-AI-Memory/memdocs/discussions
• Documentation: See README, CONTRIBUTING, CHANGELOG

🙏 Call for Early Adopters

We're seeking early adopters to:

• Validate the tool in real-world projects
• Provide feedback on API ergonomics
• Report edge cases and bugs
• Share use cases and success stories

If you try MemDocs, please let us know how it goes! Your feedback will directly shape the 2.0.0 stable release.

📝 Full Changelog

See CHANGELOG.md for complete version history.

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

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Installation: pip install memdocs==2.0.0b0

Next Steps: After user validation, we'll release 2.0.0 stable with API stability guarantees.