How to Use the Levo.ai (API Security & Observability) MCP in OpenAI Agents SDK

Q: How does OpenAI Agents SDK handle schema extraction via Levo.ai (API Security & Observability)?

The agent calls exportopenapispec to fetch live, auto-generated OpenAPI specs. It uses these specs to verify that your actual runtime deployments match your design files.

Secure your APIs directly from OpenAI Agents SDK by auditing endpoints and monitoring live data leaks.

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Connect Levo.ai (API Security & Observability) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Levo.ai (API Security & Observability) 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.

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Setup Levo.ai (API Security & Observability) with OpenAI Agents SDK

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Audit live endpoints using the MCP Server

`list_catalog_endpoints` identifies REST, GraphQL, gRPC, and SOAP endpoints across your infrastructure. Your OpenAI agents use this tool to map out the entire attack surface and find shadow APIs that standard documentation misses. The agent then runs `list_environments` to pin down where these endpoints live. By matching environments to actual endpoints, your system catches untracked services before they expose private data.

OpenAI Agents SDK monitors active vulnerabilities

`list_vulnerabilities` pulls active API security vulnerabilities discovered across your tracked applications. Your agent reads this data to flag critical OWASP risks during development runs or live monitoring sessions. It calls `get_vulnerability` to extract the diagnostic evidence for any flagged threat. This lets your agent provide exact payload examples to developers instead of vague alerts.

Track sensitive data flows via the MCP Server

`list_sensitive_data` categorizes endpoints exposing sensitive or regulated data flows like PII or PHI. Your agent scans these data flows to verify that authentication is actually active on high-risk paths. Using `get_endpoint_details`, the agent checks the exact schema structure of those sensitive routes. You get instant validation of payload structures without manual schema inspections.

Setup guide

Set up Levo.ai (API Security & Observability) MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Levo.ai (API Security & Observability) tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Levo.ai (API Security & Observability) tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Levo.ai (API Security & Observability) tools and returns structured results. Copy the full example on the right to get started.

agent.py

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="Levo.ai (API Security & Observability) Agent",
            instructions="You have access to Levo.ai (API Security & Observability) tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Levo.ai (API Security & Observability) MCP in OpenAI Agents SDK

You install the SDK and register the MCP Server URL using MCPServerStreamableHttp. The agent auto-discovers tools like list_applications to inspect your services during conversations.

Yes, you control access at the agent configuration level. If you only want the agent to read issues, expose list_vulnerabilities and omit write tools.

The agent calls export_openapi_spec to fetch live, auto-generated OpenAPI specs. It uses these specs to verify that your actual runtime deployments match your design files.

No. Setting cacheToolsList=True prevents the agent from refetching the tool definitions on every turn, keeping latency low.

Vinkius runs the server in an ephemeral sandbox that handles authentication tokens out of band. Your actual API schemas, PII markers, and vulnerability payloads never persist inside the LLM context.

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