- query_point: reverse-maps pixel RGB through colormap to recover exact
data values at geographic coordinates
- get_time_series: fetches imagery across evenly-spaced dates for
temporal analysis (up to 12 frames)
- Auto-detect polar stereographic projection (EPSG:3413/3031) for
high-latitude bounding boxes
- Add progress reporting to all HTTP-calling tools
- Add quantitative_snapshot and seasonal_timelapse prompts
- Update README with 3 new conversational examples
- 92 tests passing
Five new prompts guide LLMs through multi-tool workflows:
satellite_snapshot, climate_monitor, layer_deep_dive,
multi_layer_story, polar_watch. README documents all 11 tools,
5 resources, and 7 prompts with example conversations.
MIT license, project URLs, and updated classifiers for PyPI.
Replace hand-rolled base64 dicts with FastMCP's Image() helper in
get_imagery, compare_dates, get_imagery_composite, and get_legend.
FastMCP handles base64 encoding and MIME type automatically.
Add Context progress reporting to imagery tools so MCP clients can
display fetch status (resolving location, fetching imagery, etc).
Add dynamic resources:
gibs://colormap/{layer_id} — colormap explanation text
gibs://dates/{layer_id} — date range + live DescribeDomains
Remove unused base64 import.
