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Upstream Lens MCP Server for Pydantic AIGive Pydantic AI instant access to 8 tools to Check Api Health, Get Organization Info, Get Property Details, and more

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Upstream Lens through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this App Connector for Pydantic AI

The Upstream Lens app connector for Pydantic AI is a standout in the Data Analytics category — giving your AI agent 8 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Upstream Lens "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Upstream Lens?"
    )
    print(result.data)

asyncio.run(main())
Upstream Lens
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 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.

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.

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.

The Upstream Lens MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 8 Upstream Lens tools available for Pydantic AI

When Pydantic AI connects to Upstream Lens through Vinkius, your AI agent gets direct access to every tool listed below — spanning satellite-imagery, environmental-monitoring, remote-sensing, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

check_api_health

Check Lens API health

get_organization_info

Get organization metadata

get_property_details

Get details for a specific property feature

list_portfolios

List all portfolios

list_project_notes

Can be filtered by update date. List observations and notes for a project

list_project_observations

List detailed project observations

list_projects

List all environmental projects

list_property_imagery

) for a specific property. List available imagery layers for a property

Connect Upstream Lens to Pydantic AI via MCP

Follow these steps to wire Upstream Lens into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 8 tools from Upstream Lens with type-safe schemas

Why Use Pydantic AI with the Upstream Lens MCP Server

Pydantic AI provides unique advantages when paired with Upstream Lens through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Upstream Lens integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Upstream Lens connection logic from agent behavior for testable, maintainable code

Upstream Lens + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Upstream Lens MCP Server delivers measurable value.

01

Type-safe data pipelines: query Upstream Lens with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Upstream Lens tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Upstream Lens and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Upstream Lens responses and write comprehensive agent tests

Example Prompts for Upstream Lens in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Upstream Lens immediately.

01

"List all active environmental projects in my Lens account."

02

"Show me the latest field notes for the 'Amazon Restoration' project."

03

"List available satellite imagery layers for property 'feat_10293'."

Troubleshooting Upstream Lens MCP Server with Pydantic AI

Common issues when connecting Upstream Lens to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Upstream Lens + Pydantic AI FAQ

Common questions about integrating Upstream Lens MCP Server with Pydantic AI.

01

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.
02

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.
03

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.