# Open AI Agents x Dappier MCP
Source: https://docs.dappier.com/integrations/open-ai-agents-dappier-mcp-integration



## Overview

The integration of **OpenAI Agents SDK** and the **Dappier MCP Server** empowers developers to build **real-time, tool-augmented AI applications** by combining agentic reasoning with **dynamic, rights-cleared data**. Through the use of the **Model Context Protocol (MCP)**, OpenAI agents can seamlessly connect to the Dappier MCP Server, gaining access to tools for **real-time search, recommendations, and domain-specific insights**.

## Real-Life Implementations

### Explore These Cookbooks for Step-by-Step Implementations:

* **[Smart Content Curator with OpenAI Agents + Real-Time AI Recommendations via Dappier MCP](https://docs.dappier.com/cookbook/recipes/open-ai-agent-mcp-news-letter)** – A real-time **LLM-powered newsletter assistant** that pulls **AI-powered content recommendations** across **sports**, **lifestyle**, and **pet care**, and formats them into newsletter-ready summaries.
* **[AI Stock Analyst with OpenAI Agents + Real-Time Financial Insights via Dappier MCP](https://docs.dappier.com/cookbook/recipes/open-ai-agent-mcp-stock-analyst)** – Build a dynamic **Stock Analyst Agent** that analyzes a chosen **tech sector**, summarizes trends, and recommends an investment strategy using **live financial signals**.
* **[Dynamic Travel Planner with OpenAI Agents + Real-Time Insights via Dappier MCP](https://docs.dappier.com/cookbook/recipes/open-ai-agent-mcp-travel-assistant)** – A practical **travel planning assistant** that creates multi-day itineraries using **live weather, hotel, and event data** through Dappier’s real-time tools.

## OpenAI Agents

The **OpenAI Agents SDK** supports the **Model Context Protocol**, allowing agents to dynamically connect to and use external tool servers such as the **Dappier MCP Server**. This lets developers build flexible agents that can adapt to new tools and data contexts without hardcoding.

### Features of OpenAI Agents SDK:

* **Agents** – Modular, instruction-following LLMs with tool access.
* **MCP Integration** – Connect agents to local or remote MCP-compliant servers.
* **Tool Caching** – Reduce latency by caching tool metadata between runs.
* **Tracing** – Built-in support for tracking tool calls and debugging usage.

***

## Dappier MCP Server

The **Dappier MCP Server** is a **locally-run tool server** that exposes Dappier’s proprietary, real-time data tools through the **Model Context Protocol (MCP)**. It enables agents to become experts in finance, news, sports, and lifestyle topics by tapping into Dappier’s premium, structured data sources.

### Key Features of Dappier MCP Server:

* **Real-Time Web Search** – Google-style web results, weather, travel, and financial market queries.
* **Stock Market Tools** – Live financial data, trades, stock prices, and breaking news.
* **AI-Powered Recommendations** – Personalized and trending content across domains like sports, pet care, and sustainability.
* **Structured Output** – Clean JSON responses with rich metadata and source links.

> **Explore Dappier's data and AI models at** [marketplace.dappier.com](https://marketplace.dappier.com).

***

## Why Integrate OpenAI Agents SDK with Dappier MCP?

By integrating OpenAI agents with the Dappier MCP Server, developers can:

* **Connect agents to real-time tools** with no need for custom tool interfaces.
* **Provide dynamic, verified insights** to reduce hallucinations.
* **Build adaptive agents** that fetch content and analysis on-demand.
* **Leverage a standardized protocol (MCP)** to simplify AI tool orchestration.

### Example Use Cases:

1. **Market Intelligence Bots** – Use tools like `dappier_real_time_search` to scan for **breaking stock updates**.
2. **Content Curation Assistants** – Deploy agents that recommend trending articles and personalized news using `dappier_ai_recommendations`.
3. **Query-Driven AI Assistants** – Answer questions like “What’s trending today in tech?” with fresh data pulled at runtime.
4. **Domain-Specific Reasoners** – Turn any agent into a **finance, sports, or travel specialist** using the appropriate tool set.

***

## Basic Use Case: OpenAI Agents SDK + Dappier MCP Server

### Setup API Keys

You'll need to set up your API keys for OpenAI and Dappier.\
This ensures that the tools can interact with external services securely.

You can go to [here](https://platform.dappier.com/profile/api-keys) to get API Key from Dappier with **free** credits.

```bash  theme={null}
export DAPPIER_API_KEY="your-api-key"
```

You can go to [here](https://platform.openai.com/settings/organization/api-keys) to get API Key from OpenAI.

```bash  theme={null}
export OPENAI_API_KEY="your-api-key"
```

### Using Dappier MCP Server with OpenAI Agent (Python Code Example)

```python Python theme={null}
import asyncio
import os

from agents import Agent, Runner, trace
from agents.mcp import MCPServer, MCPServerStdio

async def run(mcp_server: MCPServer):
    agent = Agent(
        name="Assistant",
        instructions="Always respond in haiku form. You are an expert assistant that can answer real-time questions using Dappier's tools.",
        mcp_servers=[mcp_server]
    )

    result = await Runner.run(starting_agent=agent, input="How is the weather today in Austin, TX?")
    
    print(result.final_output)


async def main():
    async with MCPServerStdio(
        cache_tools_list=True,
        params={
            "command": "uvx",
            "args": ["dappier-mcp"],
            "env": {"DAPPIER_API_KEY": os.environ["DAPPIER_API_KEY"]},
        },
    ) as server:
        with trace(workflow_name="Dappier MCP usage example"):
            await run(server)

asyncio.run(main())
```

```json  theme={null}
Chilly morning air,  
Austin at fifty-three now,  
Light jacket advised. 🌤️
```

***

## Conclusion

Integrating the **OpenAI Agents SDK** with the **Dappier MCP Server** allows developers to build powerful, real-time AI agents that use live, structured data from trusted sources. Whether your application needs **financial monitoring**, **personalized content recommendations**, or **real-time web search**, this combination provides a flexible and production-ready solution using the **Model Context Protocol**.