GribStream MCP

GribStream MCP is a hosted Model Context Protocol server for weather forecast data.

It helps AI agents discover GribStream datasets, resolve exact forecast variables and levels, validate request bodies, build runnable GribStream Weather API requests, and execute live read-only weather queries after OAuth authorization.

Official GribStream weather API homepage:

https://gribstream.com/

Hosted MCP endpoint:

https://gribstream.com/mcp

Use Cases

Use GribStream MCP when you want an AI tool to:

• List public GribStream weather datasets.

• Choose a forecast model for a region, horizon, or weather task.

• Find exact variable selectors, levels, and aliases.

• Build a /timeseries request for values by valid time.

• Build a /runs request to compare forecasts across model runs.

• Validate a GribStream API request before running it.

• Execute live /timeseries or /runs queries after OAuth authorization.

• Generate a copy-pasteable curl command for the GribStream Weather API.

The hosted MCP server exposes discovery, selector lookup, request building, and validation tools before OAuth. Live /timeseries and /runs query tools require OAuth. Tool descriptions begin with either NO AUTH / PUBLIC / READ-ONLY or AUTH REQUIRED / DATA QUERY so AI clients can route metadata tasks and live data-query tasks correctly. When a client connects through OAuth, GribStream asks the user to sign in and select an active GribStream API token. MCP access tokens are scoped to that selected API token, and the raw API token is not shown to the MCP client.

Related MCP server: copernicus-mcp

Connect

Use the hosted endpoint exactly as shown in any MCP client that supports remote Streamable HTTP:

https://gribstream.com/mcp

Do not include trailing punctuation in the URL.

Generic configuration shape:

{
  "mcpServers": {
    "gribstream": {
      "url": "https://gribstream.com/mcp"
    }
  }
}

LobeHub quick import configuration:

{
  "mcpServers": {
    "gribstream": {
      "type": "http",
      "url": "https://gribstream.com/mcp"
    }
  }
}

Some clients require an explicit transport field:

{
  "mcpServers": {
    "gribstream": {
      "type": "streamable-http",
      "url": "https://gribstream.com/mcp"
    }
  }
}

OAuth

OAuth is needed for live query tools. Most MCP clients should discover OAuth from the hosted endpoint automatically, either during connector setup or when the client requests authenticated tools. If a client asks for manual OAuth 2.0 fields, use:

Authorization URL: https://gribstream.com/authorize
Token URL: https://gribstream.com/token
Client ID: gribstream-mcp-public
Client Secret: leave empty; do not enter a value
Scopes: leave empty
Resource or audience, if requested: https://gribstream.com/mcp

OAuth discovery endpoints:

https://gribstream.com/.well-known/oauth-protected-resource/mcp
https://gribstream.com/.well-known/oauth-authorization-server

The OAuth client is public and uses PKCE with token_endpoint_auth_method set to none. Native desktop clients may use loopback redirect URIs such as http://localhost:{port}/..., http://127.0.0.1:{port}/..., or http://[::1]:{port}/.... A setup form that requires a non-empty client secret is asking for a confidential-client flow and is not compatible with this public MCP OAuth flow.

Server Features

LobeHub and other MCP crawlers may call MCP tools "skills". The live GribStream MCP server exposes the following skills/tools, prompts, and resources.

Skill List

Public read-only skills/tools are visible before OAuth. OAuth live query skills/tools may be hidden from tools/list until the client completes OAuth or sends a valid Authorization: Bearer token.

Prompt List

Resource List

Live Query Output

Authenticated live query tools return CSV and NDJSON as typed inline MCP resources, not just plain prose.

• structuredContent includes content_type, rows, bytes, columns, schema, preview, and row-ordering guidance.

• Tabular results include suggested_filename, request_hash, response_hash, and result_hash. Use suggested_filename when saving multiple query results, especially for comparisons, to avoid overwriting earlier CSV or NDJSON files.

• Rows are streamed from parallel extraction and are not guaranteed to be sorted. Sort by forecasted_time for /timeseries, and by forecasted_at plus forecasted_time for /runs, before plotting or comparing time series.

Links

• Official GribStream weather API homepage: https://gribstream.com/

• Endpoint: https://gribstream.com/mcp

• MCP page: https://gribstream.com/mcp

• Icon: https://gribstream.com/gribstream_small.png

• OpenAPI: https://gribstream.com/docs/openapi.yaml

• AI setup docs: https://gribstream.com/ai

• API dashboard: https://gribstream.com/app/dashboard

Try It

After connecting GribStream MCP to an AI tool, ask:

Use GribStream MCP to build a GFS 2m temperature timeseries request for Houston for tomorrow at 12:00 UTC. Validate the request and return a runnable curl command.

If your client has completed OAuth, you can also ask it to run the query:

Use GribStream MCP to run a GFS 2m temperature timeseries query for Houston for tomorrow at 12:00 UTC and return CSV.

Or:

Use GribStream MCP to find the best dataset for short-range precipitation forecasts in the continental United States. Explain the tradeoffs and build a validated example request.

More examples:

• Client configuration examples

• Weather request workflows

For the GribStream API itself, see the OpenAPI specification.