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Planet Labs MCP Server for Windsurf 12 tools — connect in under 2 minutes

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Windsurf brings agentic AI coding to a purpose-built IDE. Connect Planet Labs through Vinkius and Cascade will auto-discover every tool. ask questions, generate code, and act on live data without leaving your editor.

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Classic Setup·json
{
  "mcpServers": {
    "planet-labs": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Planet Labs MCP Server

Connect your Planet Labs API to any AI agent and take full control of daily satellite imagery search, discovery, automated delivery, and imagery analysis through natural conversation.

Windsurf's Cascade agent chains multiple Planet Labs tool calls autonomously. query data, analyze results, and generate code in a single agentic session. Paste Vinkius Edge URL, reload, and all 12 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.

What you can do

  • Quick Search — Search for satellite imagery with geometry, date range, cloud cover, and sun elevation filters
  • Saved Searches — Create and manage saved searches for recurring imagery monitoring workflows
  • Search Results — Execute saved searches with pagination and sorting to retrieve imagery results
  • Search Statistics — Get histograms of imagery availability by time interval for planning analysis
  • Item Details — View detailed metadata for specific imagery items including acquisition conditions
  • Asset Discovery — List all available asset types (visual, analytic, UDM2) for each imagery item
  • Item Types — Browse all available satellite imagery types (PSScene, SkySat, RapidEye, Landsat, Sentinel-2)
  • Asset Types — Understand available data products (true-color, surface reflectance, uncertainty masks)
  • Cloud Coverage — Estimate clear area percentage before downloading imagery for quality assessment
  • Subscriptions — List and create automated subscriptions for continuous cloud delivery of imagery
  • Multi-Satellite Access — Search across PlanetScope (3-5m), SkySat (sub-meter), RapidEye (5m), Landsat (30m), and Sentinel-2 (10m)
  • Global Daily Coverage — Access daily imagery of Earth landmass with 200+ PlanetScope satellites

The Planet Labs MCP Server exposes 12 tools through the Vinkius. Connect it to Windsurf in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Planet Labs to Windsurf via MCP

Follow these steps to integrate the Planet Labs MCP Server with Windsurf.

01

Open MCP Settings

Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"

02

Add the server

Paste the JSON configuration above into mcp_config.json

03

Save and reload

Windsurf will detect the new server automatically

04

Start using Planet Labs

Open Cascade and ask: "Using Planet Labs, help me...". 12 tools available

Why Use Windsurf with the Planet Labs MCP Server

Windsurf provides unique advantages when paired with Planet Labs through the Model Context Protocol.

01

Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention

02

Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively

03

JSON-based configuration means zero code changes: paste a URL, reload, and all 12 tools are immediately available

04

Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts

Planet Labs + Windsurf Use Cases

Practical scenarios where Windsurf combined with the Planet Labs MCP Server delivers measurable value.

01

Automated code generation: ask Cascade to fetch data from Planet Labs and generate models, types, or handlers based on real API responses

02

Live debugging: query Planet Labs tools mid-session to inspect production data while debugging without leaving the editor

03

Documentation generation: pull schema information from Planet Labs and have Cascade generate comprehensive API docs automatically

04

Rapid prototyping: combine Planet Labs data with Cascade's code generation to scaffold entire features in minutes

Planet Labs MCP Tools for Windsurf (12)

These 12 tools become available when you connect Planet Labs to Windsurf via MCP:

01

create_saved_search

Accepts the same filter parameters as quick_search including geometry, date range, cloud cover, and item types. Returns a search ID that can be used with get_search_results to execute the search on demand. Essential for automated monitoring, change detection workflows, and recurring imagery retrieval. AI agents should use this when users ask "set up a search for new imagery over my field every week", "create a saved search for cloud-free images", or need to establish recurring imagery monitoring for a specific area. Create a saved search for continuous imagery monitoring

02

create_subscription

Accepts geometry, date range, cloud cover filters, item types, and delivery destination (cloud storage or webhook). Returns the created subscription with ID and status. Essential for setting up automated monitoring, establishing continuous data feeds for change detection, and ensuring regular imagery delivery for operational workflows. AI agents should use this when users ask "set up daily imagery delivery for my farm", "create a subscription for cloud-free images over this area", or need to establish automated imagery delivery for monitoring applications. Create a new subscription for continuous automated imagery delivery

03

get_cloud_coverage

Returns clear percentage, cloud percentage, and status information. Essential for quality assessment before downloading imagery, filtering cloudy images from analysis workflows, and ensuring usable imagery for visual interpretation. AI agents should use this when users ask "how cloudy is this image", "what percentage of this scene is clear", or need to assess imagery quality before committing to download. Estimate cloud coverage and clear area percentage for a specific imagery item

04

get_item_assets

Each asset includes download URLs, file sizes, and permissions. Essential for selecting the appropriate data product for analysis, downloading imagery for GIS processing, and understanding available data products. AI agents should use this when users ask "what assets are available for this image", "get download URLs for analytic imagery", or need to select specific asset types (visual for display, analytic for analysis) for download. List all available asset types (visual, analytic, UDM) for a specific imagery item

05

get_item_details

Essential for evaluating image quality before download, understanding acquisition conditions, and preparing orders for specific imagery. AI agents should reference this when users ask "show me details for this image", "what is the cloud cover and acquisition time for item X", or need to evaluate imagery quality before downloading. Get detailed metadata for a specific satellite imagery item

06

get_search_results

Supports pagination (page, page_size) and sorting (acquired asc/desc, published asc/desc). Returns imagery items with acquisition dates, cloud cover, geometry, and available asset types. Essential for retrieving results from pre-configured monitoring searches and executing recurring imagery queries. AI agents should use this when users ask "run my Weekly Farm Monitoring search", "get results from saved search X", or need to execute a saved search and retrieve the latest imagery results. Execute a saved search and retrieve imagery results

07

get_search_statistics

Essential for understanding imagery availability patterns, planning data collection schedules, and assessing temporal coverage for change detection analysis. AI agents should use this when users ask "how many images are available per month for my area", "show me imagery availability statistics", or need to understand temporal patterns of satellite coverage before setting up monitoring. Get statistical histograms of available imagery for an area and time period

08

list_asset_types

Returns asset type IDs, display names, and descriptions. Essential for selecting the appropriate data product for specific use cases (visual for visualization, analytic for NDVI calculation, UDM for quality filtering). AI agents should reference this when users ask "what asset types can I download", "difference between analytic and visual assets", or need to understand available data products for analysis. List all available asset types (visual, analytic, UDM, etc.) and their properties

09

list_item_types

Returns item type IDs, display names, and supported asset types for each. Essential for understanding available imagery sources, selecting appropriate resolution and coverage for analysis, and planning data acquisition strategies. AI agents should use this when users ask "what satellite imagery types are available", "compare PSScene vs SkySat resolution", or need to understand the full catalog of Planet imagery options. List all available satellite imagery item types and their supported assets

10

list_saved_searches

Returns search names, IDs, filter criteria, item types, and creation dates. Essential for managing monitoring workflows, reviewing existing search configurations, and selecting searches for execution. AI agents should reference this when users ask "show me all my saved searches", "list my monitoring configurations", or need to review existing saved searches before executing them. List all saved searches in your Planet account

11

list_subscriptions

Returns subscription names, IDs, filter criteria, delivery destinations, and status. Essential for monitoring automated imagery delivery, reviewing subscription configurations, and managing continuous data feeds. AI agents should reference this when users ask "show me all my subscriptions", "list automated imagery deliveries", or need to review existing subscription configurations. List all active imagery subscriptions for continuous cloud delivery

12

quick_search

Supports item types including PSScene (PlanetScope, 3-5m resolution, daily global coverage), SkySat (sub-meter resolution, high-detail), RapidEye (5m resolution, historical archive), Landsat 8/9 (30m resolution, USGS), and Sentinel-2 (10m resolution, ESA). Returns imagery items with acquisition dates, cloud cover percentages, sun elevation, instrument mode, geometry, and available asset types. Essential for satellite imagery discovery, change detection analysis, disaster monitoring, and agricultural assessment. AI agents should use this when users ask "find cloud-free imagery over this area from last month", "search for PSScene images of my farm", or need to discover available satellite imagery for a specific location and time period. Geometry must be provided as GeoJSON (Point, Polygon, or MultiPolygon). Date filtering uses the acquired property in ISO 8601 format. Cloud cover and sun elevation are filtered using the filter object with range operators. Search for satellite imagery from Planet Labs with geometry, date, and cloud cover filters

Example Prompts for Planet Labs in Windsurf

Ready-to-use prompts you can give your Windsurf agent to start working with Planet Labs immediately.

01

"Find cloud-free PSScene imagery over my farm boundary from the last 30 days."

02

"Show me what satellite imagery types are available and their resolutions."

03

"Create a daily subscription for cloud-free imagery over my monitoring area."

Troubleshooting Planet Labs MCP Server with Windsurf

Common issues when connecting Planet Labs to Windsurf through the Vinkius, and how to resolve them.

01

Server not connecting

Check Settings → MCP for the server status. Try toggling it off and on.

Planet Labs + Windsurf FAQ

Common questions about integrating Planet Labs MCP Server with Windsurf.

01

How does Windsurf discover MCP tools?

Windsurf reads the mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.
02

Can Cascade chain multiple MCP tool calls?

Yes. Cascade is an agentic system. it can plan and execute multi-step workflows, calling several tools in sequence to accomplish complex tasks without manual prompting between steps.
03

Does Windsurf support multiple MCP servers?

Yes. Add as many servers as needed in mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.

Connect Planet Labs to Windsurf

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.