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Search, preview, and measure Umbra open SAR from any MCP client. Umbra ships no search API.
Umbra open SAR archive is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 78/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding Umbra open SAR archive to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
mcp add io.github.reesehammer/umbra-mcp https://api.umbra-py.space/mcpReview the upstream source before running this command.
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2026-10-26T21:44:00.174192Z",
"publishedAt": "2026-10-26T21:44:00.174192Z",
"statusChangedAt": "2026-10-26T21:44:00.174192Z"
}
},
"server": {
"name": "io.github.reesehammer/umbra-mcp",
"_meta": {
"io.modelcontextprotocol.registry/publisher-provided": {
"command": "uvx --from 'umbra-py[mcp]' umbra-mcp",
"documentation": "https://github.com/reesehammer/umbra-py#drive-it-from-an-ai-agent-mcp"
}
},
"title": "Umbra open SAR archive",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"remotes": [
{
"url": "https://api.umbra-py.space/mcp",
"type": "streamable-http"
}
],
"version": "0.1.4",
"packages": [
{
"version": "0.1.4",
"transport": {
"type": "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",
"isSecret": true,
"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",
"isSecret": true,
"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",
"isSecret": true,
"description": "Alternative provider for the same two model tools, and the encoder behind find_similar_text."
}
]
}
],
"repository": {
"url": "https://github.com/reesehammer/umbra-py",
"source": "github"
},
"description": "Search, preview, and measure Umbra open SAR from any MCP client. Umbra ships no search API."
}
}