How to Use the Pet Stress Score Analyzer MCP in OpenAI Agents SDK
Build deployed pet wellness agents with the OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Pet Stress Score Analyzer MCP to OpenAI Agents SDK
Create your Vinkius account to connect Pet Stress Score Analyzer to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Key Capabilities
Score Pet Stress for Production Agents
The `calculate_stress_score` tool takes raw observational inputs and gives your agent an estimated stress score. This lets you move beyond simple guesswork; the output is a measurable number that dictates the next steps in your pet care workflow. When building complex agents, this capability means reliable guardrails. Your client can use the calculated score to decide if human review or immediate preventative action is needed before sending out recommendations.
Identify Environmental Triggers on Demand
Don't just treat symptoms; find the source. The agent uses `query_probable_triggers` to pinpoint specific environmental factors that are causing distress, like certain noises or times of day. This is critical for creating targeted intervention plans. For instance, if a pet shows signs of discomfort only when near a loud vacuum cleaner, this tool tells you exactly what triggered it, letting your agent write much more precise advice.
Write Actionable Pet Care Plans
The `generate_management_suggestions` function writes out concrete environmental modifications that owners can actually implement. It doesn't just say 'make it better'; it provides steps, like adding a specific type of enrichment toy or changing the feeding schedule. This is huge for your deployed product because the output isn't vague advice; it’s an immediate action list ready to be consumed by another agent in your workflow.
Set up Pet Stress Score Analyzer MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all Pet Stress Score Analyzer tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Pet Stress Score Analyzer tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Pet Stress Score Analyzer tools and returns structured results. Copy the full example on the right to get started.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse
async def main():
async with MCPServerSse(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as server:
agent = Agent(
name="Pet Stress Score Analyzer Agent",
instructions="You have access to Pet Stress Score Analyzer tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Pet Stress Score Analyzer. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Pet Stress Score Analyzer MCP in OpenAI Agents SDK
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