Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
Search, save, and download satellite scenes from ISRO's Bhoonidhi portal in natural language.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"bhoonidhi": {
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add bhoonidhi -- uvx bhoonidhi-mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"bhoonidhi": {
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"bhoonidhi": {
"type": "stdio",
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月8日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント geovicco-dev で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.3.0)がレジストリに届いたのは2 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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.