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Overview

Terrafloww provides a Model Context Protocol (MCP) server that enables AI agents to interact with the Marketplace. Your agent can search datasets, retrieve code examples, and understand data schemas.

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Connection Details

Connect your AI agent to the Terrafloww MCP server:
EndpointURL
SSE Endpointhttps://api.terrafloww.com/api/mcp/sse
Message Endpointhttps://api.terrafloww.com/api/mcp/message

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Authentication

The MCP server requires authentication via:
  • API Token - Include in the Authorization header
  • Session Cookie - For browser-based integrations
Authorization: Bearer your_api_token_here

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Available Tools

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search_datasets

Search for datasets within the Terrafloww catalog. Arguments:
ArgumentTypeRequiredDescription
querystringNoSearch query. Use * to list all datasets
limitnumberNoMax results (default: 10, max: 50)
Example: 
{
  "name": "search_datasets",
  "arguments": {
    "query": "sentinel-2 cloud cover",
    "limit": 5
  }
}
Response: 
[
  {
    "id": "terrafloww/sentinel-2-l2a",
    "slug": "sentinel-2-l2a",
    "name": "Sentinel-2 Level 2A",
    "description": "Surface reflectance imagery",
    "org_slug": "terrafloww"
  }
]

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get_dataset_code_example

Get a Python code snippet to access a dataset using the Rasteret library. Arguments:
ArgumentTypeRequiredDescription
dataset_slugstringYesDataset slug
org_slugstringNoOrganization slug (optional if authenticated)
Example: 
{
  "name": "get_dataset_code_example",
  "arguments": {
    "dataset_slug": "sentinel-2-l2a",
    "org_slug": "terrafloww"
  }
}
Response: 
Dataset Reference: terrafloww/sentinel-2-l2a

Spatial Extent: [-180, -90, 180, 90]
Temporal Coverage: 2015-06-27/..

Available Bands:
- B02
- B03
- B04
- B08

Code Snippet:
import rasteret

ds = rasteret.get_xarray(
    geometries=[bbox],
    bands=["B02", "B03", "B04", "B08"],
    date_range=("2025-01-01", "2025-01-31"),
    dataset="terrafloww/sentinel-2-l2a",
    cloud_cover_lt=20,
)

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get_dataset_yaml_schema

Get the JSON schema for dataset YAML definitions. Arguments: None Example: 
{
  "name": "get_dataset_yaml_schema",
  "arguments": {}
}
Returns a complete JSON schema describing all available fields for dataset configuration.

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IDE Integration

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VS Code with Continue

Add to your ~/.continue/config.json: 
{
  "mcpServers": [
    {
      "name": "terrafloww",
      "transport": {
        "type": "sse",
        "url": "https://api.terrafloww.com/api/mcp/sse",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  ]
}

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Claude Desktop

Add to your Claude Desktop configuration: 
{
  "mcpServers": {
    "terrafloww": {
      "command": "npx",
      "args": ["-y", "@anthropic/mcp-proxy"],
      "env": {
        "MCP_TRANSPORT": "sse",
        "MCP_URL": "https://api.terrafloww.com/api/mcp/sse",
        "MCP_HEADERS": "Authorization:Bearer YOUR_API_TOKEN"
      }
    }
  }
}

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Use Cases

Dataset Discovery

Let your AI agent search and explore available geospatial datasets.

Code Generation

Get ready-to-use Python snippets for accessing specific datasets.

Schema Understanding

Help your agent understand how to create and configure datasets.

Workflow Automation

Build automated pipelines that interact with the Marketplace.

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Next Steps

Creating Datasets

Learn the YAML schema for dataset definitions.

Using Datasets

Access data with the Rasteret library.