JAXA Earth API v0.1.5 Adds MCP for GenAI Integration

🔑 Enhanced Key Takeaways

• •MCP support enables four specific functions in Claude Desktop: search_collections_id for collection details, show_images for satellite imagery display, calc_spatial_stats for spatial statistics, and show_spatial_stats for results visualization.[1][5]
• •Installation for MCP requires pip install of jaxa-earth package, mcp dependency, and a custom mcp_server.py script configured with venv Python executable for Claude Desktop integration.[5]
• •API uses ImageCollection class with methods like filter_date, filter_resolution, filter_bounds, select, and get_images for querying datasets such as JAXA.EORC_ALOS.PRISM_AW3D30.v3.2_global.[1]

🛠️ Technical Deep Dive

• •ImageCollection object supports STAC-based filtering with properties stac_date (updated via filter_date with date_lim list), stac_ppu (updated via filter_resolution with float ppu), stac_bounds (updated via filter_bounds), stac_band, and raster; defaults to None.[1]
• •ImageProcess class processes output from get_images() to enable show_images() for visualization, calc_spatial_stats() for statistics computation, and show_spatial_stats() for stats display.[1]
• •MCP server tools expose JAXA Earth API functions directly in Claude Desktop after installing jaxa-earth-0.1.5.zip, mcp package, and configuring mcp_server.py with venv path; requires full Claude Desktop restart.[5]

🔮 Future ImplicationsAI analysis grounded in cited sources

⏳ Timeline