How to Use the API Ninjas MCP in OpenAI Agents SDK

Plug API Ninjas into your OpenAI Agents SDK workflow to calculate BMR, TDEE, and track nutrition with production-grade safety.

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Connect API Ninjas MCP to OpenAI Agents SDK

Create your Vinkius account to connect API Ninjas 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 API Ninjas with OpenAI Agents SDK

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Calculate metabolic stats in OpenAI Agents SDK

Feed your agent weight and activity data to get precise caloric numbers. You'll use `get_bmr`, `get_tdee`, and `get_calories_burned` to build health-tracking logic that stays within your defined guardrails. Because you're using the OpenAI Agents SDK, these tools trigger via your established execution flow. The agent handles the math internally while you maintain full tracing in your dashboard.

Search exercise libraries for OpenAI Agents SDK

Query the `get_exercises` endpoint to find routines filtered by muscle group or equipment availability. It's built for agents that need to suggest specific movements based on user constraints. Your agent parses the step-by-step instructions directly into your response. This MCP Server keeps the data structured so your agent doesn't have to guess the mechanics.

Analyze body composition with OpenAI Agents SDK

Pipe physical measurements into `get_body_fat` to get an immediate percentage and health category. It gives your agent the context needed to provide relevant feedback on user progress. Your agent checks the `get_nutrition` data alongside these stats to build a complete picture. All actions are validated before execution to ensure no bad data hits your backend.

Setup guide

Set up API Ninjas 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 API Ninjas tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate API Ninjas 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="API Ninjas Agent",
            instructions="You have access to API Ninjas 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 API Ninjas MCP in OpenAI Agents SDK

Install the necessary packages and instantiate the MCPServerStreamableHttp class. Point it to your Vinkius endpoint and pass the instance into your Agent constructor.

Yes, tools are auto-discovered by the framework. You just set cacheToolsList to true and the agent handles the rest.

Yes, but only via the tools you call. The server acts as a bridge for metrics like body fat and BMR.

Vinkius handles the heavy lifting with an endpoint token. You just provide the token to the HTTP configuration.

We only touch user-provided metrics like age, weight, and height for calculation purposes. Data isn't stored permanently; it's processed in an ephemeral sandbox and discarded.

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