Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Search, save, and download satellite scenes from ISRO's Bhoonidhi portal in natural language.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"bhoonidhi": {
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add bhoonidhi -- uvx bhoonidhi-mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"bhoonidhi": {
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"bhoonidhi": {
"type": "stdio",
"command": "uvx",
"args": [
"bhoonidhi-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 8 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub geovicco-dev, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.3.0) llegó al registro hace 2 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Up-to-date docs for AI agents
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Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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.