SkyFi MCP Server
Integration with Google ADK and Gemini for building AI agents that use SkyFi satellite imagery tools.
Integration with LangChain framework for building AI agents that use SkyFi satellite imagery tools.
Integration with LangGraph framework for building stateful AI agents that use SkyFi satellite imagery tools.
Integration with OpenAI for using SkyFi MCP tools via OpenAI's API.
Integration with Vercel AI SDK for building AI applications that consume SkyFi MCP tools.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@SkyFi MCP Server search for satellite imagery of New York City from last month"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SkyFi MCP Server
Official Model Context Protocol server for the SkyFi satellite imagery platform. Enables any AI agent to search, price, order, and monitor satellite imagery through conversational tool calls.
Quick Start (< 10 minutes)
1. Install
npm install skyfi-mcp@0.1.02. Configure
Create ~/.skyfi/config.json:
{ "api_key": "sk_your_skyfi_api_key" }Or set the environment variable:
export SKYFI_API_KEY=sk_your_key3. Run (Local STDIO)
npx skyfi-mcp4. Connect
Claude Code / Claude Desktop:
{
"mcpServers": {
"skyfi": {
"command": "npx",
"args": ["skyfi-mcp"],
"env": { "SKYFI_API_KEY": "sk_your_key" }
}
}
}Claude.ai (remote MCP — no install needed):
Open Claude.ai → Settings → Integrations → Add MCP Server
Enter the server URL:
https://skyfi-mcp.skyfi-xian.workers.dev/mcpAdd your SkyFi API key as a custom header:
X-SkyFi-API-Key: sk_your_keySave — Claude will automatically exchange your key for a session token
Remote (any framework):
# First request: send your API key to get a session token
POST https://skyfi-mcp.skyfi-xian.workers.dev/mcp
Header: X-SkyFi-API-Key: sk_your_key
→ Response includes X-MCP-Token header
# All subsequent requests: use the session token
POST https://skyfi-mcp.skyfi-xian.workers.dev/mcp
Header: X-MCP-Token: mcp_sess_<your_token>Your raw API key is only sent once. The session token has a 4-hour idle TTL (extends on each request) and 7-day max lifetime.
Related MCP server: SkyFi MCP Server
Standout Differentiators
Reliability scorecard: generated operational snapshot at
mcp-docs/STATUS.md(npm run status:refresh)Golden demo workflow: maritime monitoring showcase at
mcp-docs/GOLDEN_DEMO_MARITIME.mdCost intelligence tool:
recommend_archive_purchaseranks options by price/quality strategy with budget filtering
Authentication
Token Exchange (Remote)
The remote server uses a token exchange model to protect your SkyFi API key:
Initialize — Send
X-SkyFi-API-Keyon your first request. The server validates it and returns anX-MCP-Tokensession token.Use — All subsequent requests use
X-MCP-Token. Your raw API key never appears in agent traffic again.Expire — Session tokens expire after 4 hours idle or 7 days max. Re-send your API key to get a new one.
Service Tokens (Pipelines)
For automated pipelines that run unattended, create a long-lived service token:
# Call the create_service_token tool with an active session
→ Returns: mcp_svc_<token> (90-day lifetime, no idle expiry)Service tokens support optional scopes (restrict which tools can be called) and budget caps (server-side spend limits).
Local (STDIO)
Local mode reads your API key from ~/.skyfi/config.json or SKYFI_API_KEY env var at startup. No token exchange needed.
Tools (19)
Category | Tools |
Geocoding |
|
Discovery |
|
Pricing |
|
Cost Intelligence |
|
Ordering |
|
History |
|
Monitoring |
|
Order Safety
Orders use a two-step confirmation flow enforced server-side:
Quote → returns price and
quote_id(valid 15 min)Execute → requires
quote_id+user_confirmed: true+idempotency_key
The execute_* tools cannot be called without all three fields. This is enforced at the schema level and cannot be bypassed by prompt injection.
Security
API key protection — Raw key sent once, exchanged for scoped token. Key encrypted at rest (AES-256-GCM) with derived keys (HKDF).
Key hashing — Usage metrics use HMAC-SHA-256 with a separate derived key. Not reversible without the server secret.
Per-request isolation — Each request creates an independent SkyFi client. No shared mutable auth state. One tenant's credentials cannot leak to another.
Rate limiting — Per-key: 100 calls/min, 20/10s burst. Daily caps: 10 orders, $10K spend.
Service token scoping — Optional tool restrictions and budget caps, enforced server-side.
Prompt injection defense — All inputs treated as data. String length caps (500 chars). Control character stripping. Order confirmation enforced server-side, not in prompts.
Framework Support
Framework | Transport | Guide |
Google ADK | STDIO / HTTP+SSE | |
LangChain / LangGraph | STDIO / HTTP+SSE | |
Vercel AI SDK | HTTP+SSE | |
Claude Web | HTTP+SSE | |
OpenAI | HTTP+SSE | |
Claude Code | STDIO / HTTP+SSE | |
Gemini | HTTP+SSE |
Compatibility matrix and transport expectations: docs/integrations/COMPATIBILITY.md
Simulation Mode
Test the full order flow without placing real orders:
SKYFI_SIMULATE=true npx skyfi-mcpOr per-request: pass "simulate": true in quote/execute tool calls.
Deployment
Cloudflare Workers (live):
https://skyfi-mcp.skyfi-xian.workers.dev/mcpSelf-deploy:
npx wrangler deployDocker:
docker compose upDevelopment
npm install
npm run build # Build with tsup
npm test # Run test suite
npm run typecheck # TypeScript check
npm run lint # ESLintLicense
MIT
Available Tools
19 toolscheck_capture_feasibilityA
Analyze feasibility for a tasking order: satellite availability, revisit window, cloud cover forecast, and a plain-language summary. You MUST call this and present its output to the user before placing any tasking order. Precondition: call this before quote_tasking_order.
Inputs: aoi (required), sensor_type (required), desired_date_range.
create_webhook_subscriptionA
Register a webhook endpoint to receive push notifications when new imagery matching a monitoring rule is available. Requires an active monitor_id from setup_aoi_monitoring.
Inputs: monitor_id (required), endpoint_url (required), secret.
estimate_archive_priceA
Returns itemized pricing for a given archive order (scene, AOI, resolution) before commitment. Use this to give the user a cost estimate before generating a binding quote.
Inputs: aoi (required), scene_id (required), resolution_tier.
estimate_tasking_costA
Estimate the cost for a new satellite capture tasking order. Use this to give the user a cost preview before checking feasibility or generating a quote.
Inputs: aoi (required), sensor_type (required), resolution_tier.
execute_archive_orderADestructive
Place an archive order using a confirmed quote. Preconditions: (1) you must have a valid quote_id from quote_archive_order, (2) the user must have explicitly confirmed they want to proceed, (3) you must provide an idempotency_key (UUID) for safe retries. Do NOT call this tool autonomously — always wait for user confirmation.
Inputs: aoi (required), archive_id (required), user_confirmed (required), label.
execute_tasking_orderADestructive
Place a tasking order using a confirmed quote. Preconditions: (1) valid quote_id from quote_tasking_order, (2) explicit user confirmation, (3) idempotency_key (UUID). Do NOT call this tool autonomously — always wait for user confirmation.
Inputs: aoi (required), resolution (required), window_end (required), product_type (required), +4 more.
explore_open_dataA
Browse freely available datasets on SkyFi, filterable by provider and region. Use this when the user asks about free or open satellite data.
Inputs: page, limit, region, provider.
fetch_order_imageA
Return download URL and metadata for a completed order's imagery. Use this when the user wants to download or access imagery from a delivered order.
Inputs: order_id (required).
geocodeA
Forward geocoding: accepts a human-readable location string (e.g. 'Port of Rotterdam') and returns lat/lng coordinates. Use this when the user mentions a place by name and you need coordinates for search or ordering tools.
Inputs: query (required).
get_bounding_boxA
Returns a bounding box polygon for a named place, directly usable as an AOI in search and order tools. Use this to convert a place name into a GeoJSON polygon for subsequent tool calls.
Inputs: query (required).
get_notification_statusA
Check delivery history and status for webhook subscriptions. Use this to verify notifications are being delivered or to diagnose delivery failures.
Inputs: monitor_id, subscription_id.
get_order_statusA
Return current status and progress for an order by ID. Use this to check on a previously placed order.
Inputs: order_id (required).
list_ordersA
List the user's historical orders with filters for date range and status. Use this when the user asks about their past orders or order history.
Inputs: page, limit, status, date_range.
quote_archive_orderA
Generate a binding quote for an archive order. Returns a quote_id (valid 15 minutes) and a human-readable summary of what will be purchased and at what price. Present this to the user and wait for explicit confirmation before calling execute_archive_order.
Inputs: aoi (required), archive_id (required), overlap_sqkm (required), price_per_sqkm_usd (required), +1 more.
quote_tasking_orderA
Generate a binding quote for a new satellite capture tasking order. Returns a quote_id and summary. Precondition: call check_capture_feasibility first and present results to the user. Present this quote to the user and wait for confirmation before calling execute_tasking_order.
Inputs: aoi (required), resolution (required), window_end (required), product_type (required), +1 more.
recommend_archive_purchaseA
Rank candidate archive scenes by cost, quality, or a balanced strategy. Use this after search/pricing to pick the best scene under an optional budget.
Inputs: candidates (required), top_k, strategy, max_budget_usd.
reverse_geocodeA
Returns a place name for a given coordinate pair. Use this when you have lat/lng coordinates and need a human-readable location name.
Inputs: lat (required), lon (required).
search_archiveA
Search available satellite imagery by AOI, date range, resolution, and sensor type. Returns scenes with IDs, capture dates, cloud cover, preview URLs, and per-scene pricing. Use this as the first step when the user wants to find existing imagery.
Inputs: aoi (required), page, limit, date_range, +2 more.
setup_aoi_monitoringA
Configure recurring monitoring of an AOI for new imagery. Set sensor preferences, resolution requirements, and notification frequency. Use this when the user wants to be alerted when new imagery becomes available over a specific area.
Inputs: aoi (required), frequency, sensor_type, min_resolution_m.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 19 tools
Each tool has a clearly distinct purpose, with workflow steps (estimate vs quote vs execute) and resource types (archive vs tasking vs monitoring) cleanly separated. No two tools overlap in function; even related tools like geocode and get_bounding_box serve different output needs.
All tool names follow a consistent verb_noun pattern in snake_case, using descriptive verbs (estimate, quote, execute, get, list) and clear noun targets (archive_order, tasking_order, notification_status). There is no mixing of styles or conventions.
At 19 tools, the set is slightly above the ideal 3-15 range, but the breadth is justified by the platform covering archive ordering, tasking, monitoring, geocoding, and order management. Each tool earns its place in the workflow, and the count feels reasonable rather than bloated.
Core lifecycles are well-covered: search/explore, estimate, quote, execute, track, and retrieve for both archive and tasking orders, plus monitoring setup and geocoding utilities. Minor gaps exist, such as lacking explicit tools to cancel or update monitoring/webhook subscriptions, but these are non-critical and don't create dead ends.
Maintenance
Related MCP Connectors
Pay-per-use tool marketplace for AI agents. Search, price-check, and call APIs via MCP.
Paid intelligence tools for AI agents across risk, finance, property, logistics and more.
Flight and sky conditions for agents, from METAR/TAF and airports to aurora and satellite passes.
Web search, page reading, HTML to PDF, file upload and flight search for AI agents, paid in USDC.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to interact with SkyFi's geospatial data services for ordering satellite imagery, searching data catalogs, checking pricing and feasibility, and monitoring areas of interest.5 npmMIT
- FlicenseNot gradedqualityNot gradedmaintenanceEnables AI agents to search, order, and monitor satellite and geospatial imagery through SkyFi's API, including archive searches, pricing estimates, and order tracking.-
- AlicenseNot gradedqualityDmaintenanceIntegrates SkyFi satellite imagery and OpenStreetMap services with AI applications to enable high-resolution image searching, ordering, and area monitoring. It provides 21 tools for geospatial tasks, including geocoding, tasking quotes, and satellite pass prediction.3MIT

Planet MCPofficial
AlicenseNot gradedqualityCmaintenanceEnables AI agents to interact with the Planet API for satellite imagery ordering, subscriptions, and data management through natural language.17Apache 2.0