umbra-py MCP
An MCP server and community STAC API that allows agents to search, preview, download, and analyze Umbra open SAR data from an S3 bucket and static STAC tree, without requiring a search API or local installation of heavy dependencies.
Package and access
Local package with source-attributed installation metadata. Koskamo does not execute packages during review.
What you can do with it
- Search Umbra SAR open data by area or product type
- Preview and download SAR imagery via HTTP
- Load SAR data into xarray for analysis-ready processing
Source and maintenance
- Maintenance checked
Packages and installation
Source-provided package data. Koskamo has not executed or live-probed this package.
umbra-py 0.1.4
{
"version": "0.1.4",
"transport": "stdio",
"identifier": "umbra-py",
"runtimeHint": "uvx",
"registryType": "pypi",
"registryBaseUrl": "https://pypi.org",
"runtimeArguments": [
{
"name": "--from",
"type": "named",
"value": "umbra-py[mcp]",
"description": "The server ships inside the umbra-py distribution and needs its [mcp] extra, so the package uvx installs is not the bare identifier."
},
{
"type": "positional",
"value": "umbra-mcp",
"valueHint": "console_script",
"description": "The console script to run from that distribution ([project.scripts] in pyproject.toml)."
}
],
"environmentVariables": [
{
"name": "UMBRA_CANOPY_TOKEN",
"description": "Canopy API token. Set it and the same search tools query Umbra's authenticated commercial archive instead of the open bucket; leave it unset for the open data, which needs no credentials."
},
{
"name": "UMBRA_INDEX_DB",
"format": "filepath",
"description": "Path to a local catalog index (built with 'umbra index build' or fetched with 'umbra index fetch'). Without one the server walks the public bucket per search, which is correct but slow."
},
{
"name": "ANTHROPIC_API_KEY",
"description": "Optional. With a key, describe_scene and narrate_change call a vision model on the server. Without one they return a reading kit (picture + SAR primer) so the client's own model does the reading. A public host must not set this."
},
{
"name": "OPENAI_API_KEY",
"description": "Alternative provider for the same two model tools, and the encoder behind find_similar_text."
}
]
}Tools
Reported by the attributed source; not independently observed by Koskamo.
Connect from your client
Each snippet configures the same source-provided package; replace placeholders before use.
Cursor
{
"mcpServers": {
"umbra-py-mcp": {
"command": "uvx",
"args": [
"umbra-py==0.1.4"
],
"env": {
"UMBRA_CANOPY_TOKEN": "<YOUR_UMBRA_CANOPY_TOKEN>",
"UMBRA_INDEX_DB": "<YOUR_UMBRA_INDEX_DB>",
"ANTHROPIC_API_KEY": "<YOUR_ANTHROPIC_API_KEY>",
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}Cline
{
"mcpServers": {
"umbra-py-mcp": {
"command": "uvx",
"args": [
"umbra-py==0.1.4"
],
"env": {
"UMBRA_CANOPY_TOKEN": "<YOUR_UMBRA_CANOPY_TOKEN>",
"UMBRA_INDEX_DB": "<YOUR_UMBRA_INDEX_DB>",
"ANTHROPIC_API_KEY": "<YOUR_ANTHROPIC_API_KEY>",
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}VS Code
{
"servers": {
"umbra-py-mcp": {
"type": "stdio",
"command": "uvx",
"args": [
"umbra-py==0.1.4"
],
"env": {
"UMBRA_CANOPY_TOKEN": "<YOUR_UMBRA_CANOPY_TOKEN>",
"UMBRA_INDEX_DB": "<YOUR_UMBRA_INDEX_DB>",
"ANTHROPIC_API_KEY": "<YOUR_ANTHROPIC_API_KEY>",
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}Claude Desktop
{
"mcpServers": {
"umbra-py-mcp": {
"command": "uvx",
"args": [
"umbra-py==0.1.4"
],
"env": {
"UMBRA_CANOPY_TOKEN": "<YOUR_UMBRA_CANOPY_TOKEN>",
"UMBRA_INDEX_DB": "<YOUR_UMBRA_INDEX_DB>",
"ANTHROPIC_API_KEY": "<YOUR_ANTHROPIC_API_KEY>",
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}Let your agent find its tools
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