v0.0.5

Release v0.0.5

Changed

• Version bump - Prepared for release v0.0.5
  • All three variants (dev, PyPI, Docker) now report correct version and variant
  • Full parity achieved across all deployment methods

Highlights

• 166 tests passing with 81% coverage
• Full Docker, PyPI, and dev variant parity
• Robust version and variant reporting in health_check

Installation

# PyPI (recommended)
uvx portfolio-mcp stdio

# Docker
docker pull ghcr.io/l4b4r4b4b4/portfolio-mcp:0.0.5

# From source
git clone https://github.com/l4b4r4b4b4/portfolio-mcp.git
cd portfolio-mcp
uv run portfolio-mcp stdio

v0.0.4 - Docker Version Fix

Fixed

• Docker version detection - Docker image now properly installs the package
  • Base image: Copy uv to runtime stage for CLI usage
  • App image: Install portfolio-mcp package with uv pip install --no-deps .
  • CMD now uses uv run portfolio-mcp instead of python -m app
  • Fixes __version__ showing 0.0.0-dev instead of actual version
  • Development image uses editable install: uv pip install --no-deps -e .

Testing

After pulling new Docker image:

• health_check should show version: "0.0.4"
• health_check should show variant: "installed"

v0.0.3 - Health Check with Version Info

Changes

• ✅ health_check now returns version (from __version__)
• ✅ health_check now returns variant (dev vs installed)
• ✅ Variant detection: 0.0.0-dev = dev, else installed (PyPI/Docker)
• ✅ Updated tests to verify new fields (17 tests passing)
• ✅ Clean up Docker config and Zed settings

Testing

• All server tests pass (17/17)
• Docker images published to GHCR
• PyPI package publishing...

v0.0.2 - Fix finquant dependency

v0.0.2

Bug Fixes

• Switch from finquant (git source) to finquant-enhanced>=0.7.1 (PyPI)
• Fixes data type validation bug in portfolio creation

Installation

uvx portfolio-mcp stdio
# or
pip install portfolio-mcp

v0.0.1 - Initial Release

🚀 Initial Release of portfolio-mcp

A portfolio analysis MCP server powered by mcp-refcache.

Features

• 26 MCP Tools for comprehensive portfolio analysis
• Portfolio Management: Create, read, update, delete portfolios
• Analysis Tools: Metrics, returns, correlations, drawdowns, covariance
• Optimization: Efficient frontier, Monte Carlo simulation
• Data Sources: Yahoo Finance (stocks/ETFs), CoinGecko (crypto), Synthetic (GBM)
• Reference-Based Caching: Large datasets cached via mcp-refcache

Installation

# Via uvx (recommended)
uvx portfolio-mcp stdio

# Via pip
pip install portfolio-mcp
portfolio-mcp stdio

# Via Docker
docker run --rm -i ghcr.io/l4b4r4b4b4/portfolio-mcp:latest python -m app stdio

Quality

• 163 tests passing
• 81% code coverage
• Full type hints
• Pydantic models for all I/O