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제작자가 쓴 설명(영어 원문)
Search, save, and download satellite scenes from ISRO's Bhoonidhi portal in natural language.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"bhoonidhi": {
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add bhoonidhi -- uvx bhoonidhi-mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"bhoonidhi": {
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"bhoonidhi": {
"type": "stdio",
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 geovicco-dev 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.3.0)은 2개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
An MCP server that lets an AI agent search, save, download, and cart satellite scenes from ISRO's Bhoonidhi Browse & Order portal (NRSC) in natural language. An agent can turn a sentence like "Sentinel-2 over Shillong last January" into a real search against the live portal, see honestly what is available to download, save a search to reuse later, preview what a download would fetch, and — once logged in — download open-access scenes or stage them to the cart.
It is a thin adapter over the bhoonidhi-downloader SDK — the same client the bhd CLI uses — so no portal logic is duplicated.
Search and save with no login; download and cart with one. The tools reach the full archive of 41 satellite missions and 79 sensors, search the live portal, and save searches to reusable slugs — all without credentials. Downloading open-access scenes and staging scenes to the Bhoonidhi cart need a login, done out of band with bhd auth login (the server reuses that session).
| Tool | What it does | Login |
|---|---|---|
list_archive | The vocabulary of satellites, sensors, and search tokens the portal supports, live from Bhoonidhi. | no |
resolve_location | Turns a place name ("Loktak Lake") into a centroid and bounding box. Rejects inputs that are not place names. | no |
search_scenes | Natural-language scene search over an area and date range. Resolves a casual satellite name to exact tokens, and reports each scene's availability (Ready / Archived / OnOrder / Priced). Stateless — nothing is saved. | no |
preview_download | A dry run: shows what downloading the results would fetch, and what would be skipped, before anything is downloaded. | no |
save_query | Persists a search (same arguments as search_scenes) to a reusable slug, so it can be downloaded or staged to the cart later. | no |
list_queries | Lists saved queries as compact summaries: slug, name, date range, satellites, area, and availability. | no |
show_query | Returns one saved query by slug, with its scenes. | no |
remove_query | Deletes a saved query by slug. | no |
auth_status | Reports whether a login is configured. Never handles a password or token. | no |
download_query | Downloads a saved query's open-access scenes in the background, to a fixed server-configured root. Returns a job_id at once. | yes |
download_status | One-off check of a background download by job_id: bytes downloaded, transfer rate, percent when the size is known, and per-scene detail. | no |
download_wait | Blocks until a download finishes (or a capped timeout), then reports — the efficient primitive a background watcher loops on. | no |
cart_add | Stages a saved query's scenes to the cart (routes each to ready / on-order / priced). | yes |
cart_list | Lists scenes currently staged in the cart. | yes |
cart_remove | Removes scenes from the cart. | yes |
Availability matters: an OpenData scene is not necessarily staged for download. search_scenes and preview_download distinguish Ready (fetch it now) from Archived (open data, but may need a request on the portal first), so an agent does not over-promise.
Downloads run in the background, independent of the conversation: download_query returns a job_id at once and the transfer proceeds on its own. Check progress once with download_status — it reports bytes downloaded, a transfer rate, and a percent once the size is known — or follow a job to completion with download_wait, which blocks until it finishes (or a capped timeout) so an agent can delegate a background watcher and keep the conversation free instead of sleep-looping. A job lives only as long as the server process, so once a download proves large the status recommends running a standalone bhd query download command you own instead.
The server is a Python package with a console entry point, bhoonidhi-mcp. The simplest way to run it is with uv — uvx fetches, builds, and launches it straight from the source, no clone or virtualenv needed:
uvx --from git+https://github.com/geovicco-dev/bhoonidhi-mcp bhoonidhi-mcp
The first run builds from source; later runs start from cache. The server speaks stdio and is launched by an MCP client — you point the client at that command.
Prefer a local checkout (for development)? Clone and uv sync, then use .venv/bin/bhoonidhi-mcp as the command instead:
git clone https://github.com/geovicco-dev/bhoonidhi-mcp
cd bhoonidhi-mcp uv sync
Every MCP client needs the same thing: the command to launch. Point it at uvx with the source and entry point as arguments.
claude_desktop_config.json (or claude mcp add):
{
"mcpServers": { "bhoonidhi": { "command": "uvx", "args": ["--from", "git+https://github.com/geovicco-dev/bhoonidhi-mcp", "bhoonidhi-mcp"] } } }
~/.config/opencode/opencode.json:
{
"mcp": { "bhoonidhi": { "type": "local", "command": ["uvx", "--from", "git+https://github.com/geovicco-dev/bhoonidhi-mcp", "bhoonidhi-mcp"], "enabled": true } } }
npx @modelcontextprotocol/inspector uvx --from git+https://github.com/geovicco-dev/bhoonidhi-mcp bhoonidhi-mcp
Ask an agent, in plain language:
"What Sentinel-2 scenes are over Shillong in January 2024, and how many can I
actually download?"
The agent calls resolve_location for Shillong, then search_scenes, and answers from the result — for example, that all scenes are *Archived* (open data, but each may need a request on the portal before it will download), rather than claiming they are all ready.
Copy these into any connected agent to get a feel for what it can do.
." ." ." and let me know when it's done — I'll keep working." to my cart."Search, saved queries, and previews need no credentials. Downloading scenes and staging them to the cart do. Log in once, out of band — the server reuses the same session the bhd CLI writes:
bhd auth login
The MCP server never takes a username or password as a tool argument, and auth_status never returns your token. For a headless setup with no interactive login, you can instead set BHOONIDHI_USERNAME / BHOONIDHI_PASSWORD in the server's environment; the server reads them only to establish a session.
Set as environment variables (all optional):
| Variable | Default | Purpose |
|---|---|---|
BHOONIDHI_MCP_GEOCODER_USER_AGENT | bhoonidhi-mcp/0.3 | User-Agent sent to Nominatim (its usage policy asks for a descriptive one). |
BHOONIDHI_MCP_FUZZY_THRESHOLD | 88 | Score (0–100) a satellite-name match must clear to be confident; below it, candidates are returned for the agent to confirm. |
BHOONIDHI_MCP_MAX_RESULTS | 50 | Maximum scenes returned inline by search_scenes. |
BHOONIDHI_MCP_DOWNLOAD_ROOT | ~/Downloads | Allow-listed root every download writes under, as / /. The agent cannot choose an arbitrary path. |
BHOONIDHI_MCP_DOWNLOAD_PARALLEL | 4 | Parallel download workers. |
BHOONIDHI_MCP_LARGE_DOWNLOAD_MB | 500 | Once a download's live byte total (or known size) passes this, the status flags it large and steers the agent to hand off or run a standalone command. |
BHOONIDHI_USERNAME / BHOONIDHI_PASSWORD | *(unset)* | Optional headless login. Prefer bhd auth login; fill these out of band, never commit them. |
The imagery reached through this server belongs to ISRO/NRSC and is governed by the Bhoonidhi EULA, not by this project's MIT license — that license covers the code here, nothing else. What the EULA asks of you:
uv sync
uv run pytest # test suite uv run ruff check . # lint
MIT — see LICENSE.