Bring Satellite Imagery
to Pydantic AI
Learn how to connect Upstream Lens to Pydantic AI and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Upstream Lens MCP Server?
Connect your Upstream Tech Lens account to any AI agent and simplify how you monitor conservation projects, analyze satellite imagery, and track environmental changes through natural conversation.
What you can do
- Project & Portfolio Oversight — List all environmental projects and portfolios to manage your conservation assets.
- Imagery Analysis — Query available satellite imagery layers (Sentinel, Landsat, etc.) for specific property features.
- Geospatial Insights — Fetch detailed metadata and field observations for properties to track ground-truth data.
- Environmental Monitoring — List project notes and observations to keep a record of changes over time.
- Organization Management — Retrieve Lens organization profiles and verify account configurations.
- Operational Status — Check API health and connectivity to ensure your monitoring engine is always active.
How it works
1. Subscribe to this server
2. Enter your Upstream Tech Lens API Key (found in your account dashboard)
3. Start monitoring your environmental assets from Claude, Cursor, or any MCP client
Who is this for?
- Conservation Managers — quickly retrieve field notes and check satellite imagery availability via simple AI queries.
- Environmental Analysts — monitor changes in property features and verify geospatial metadata directly from the workspace.
- Sustainability Teams — track project observations and maintain an organized portfolio of environmental monitoring sites.
Built-in capabilities (8)
Check Lens API health
Get organization metadata
Get details for a specific property feature
List all portfolios
Can be filtered by update date. List observations and notes for a project
List detailed project observations
List all environmental projects
) for a specific property. List available imagery layers for a property
Why Pydantic AI?
Pydantic AI validates every Upstream Lens tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Upstream Lens integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your Upstream Lens connection logic from agent behavior for testable, maintainable code
Upstream Lens in Pydantic AI
Upstream Lens and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Upstream Lens to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Upstream Lens in Pydantic AI
The Upstream Lens 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. All 8 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Upstream Lens for Pydantic AI
Every tool call from Pydantic AI to the Upstream Lens MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I see if new satellite images are available for my project?
Yes! Use the list_property_imagery tool and provide the Property ID. Your agent will retrieve all available imagery layers (Sentinel, Landsat, etc.) with their respective capture dates.
How do I retrieve field notes for a specific conservation project?
Run the list_project_notes query with your Project ID. You can also provide an optional timestamp to filter only notes updated after a specific date.
Is it possible to see the geospatial metadata for a property feature?
Absolutely. Use the get_property_details tool with the Feature ID to retrieve detailed geospatial data and metadata for any monitored property.
How does Pydantic AI discover MCP tools?
Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
Does Pydantic AI validate MCP tool responses?
Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your Upstream Lens MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai