# How to integrate Pexels MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Pexels MCP with OpenAI Agents SDK",
  "toolkit": "Pexels",
  "toolkit_slug": "pexels",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/pexels/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/pexels/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:21:52.555Z"
}
```

## Introduction

This guide walks you through connecting Pexels to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Pexels agent that can find free stock photos of beaches, get trending pexels videos this week, list featured photography collections through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Pexels account through Composio's Pexels MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Pexels with

- [ChatGPT](https://composio.dev/toolkits/pexels/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/pexels/framework/antigravity)
- [Claude Agent SDK](https://composio.dev/toolkits/pexels/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/pexels/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/pexels/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/pexels/framework/codex)
- [Cursor](https://composio.dev/toolkits/pexels/framework/cursor)
- [VS Code](https://composio.dev/toolkits/pexels/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/pexels/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/pexels/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/pexels/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/pexels/framework/cli)
- [Google ADK](https://composio.dev/toolkits/pexels/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/pexels/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/pexels/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/pexels/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/pexels/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/pexels/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Pexels
- Configure an AI agent that can use Pexels as a tool
- Run a live chat session where you can ask the agent to perform Pexels operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## What is the Pexels MCP server, and what's possible with it?

The Pexels MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Pexels account. It provides structured and secure access to the Pexels media library, so your agent can search photos and videos, fetch curated collections, explore trending media, and retrieve detailed asset information on your behalf.
- Photo and video search: Instantly find high-quality photos and videos from Pexels based on keywords, categories, or filters using natural language queries.
- Curated and trending media discovery: Let your agent fetch the latest curated photos or surface popular videos to keep your content pipeline fresh and engaging.
- Collection management and exploration: Access your own collections or featured Pexels collections, and pull all media from any collection with ease.
- Detailed asset retrieval: Retrieve metadata, dimensions, and direct image or video URLs for any specific photo or video asset by ID.
- Content integration for creative workflows: Seamlessly pull media assets into your applications, presentations, or creative projects with minimal effort.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PEXELS_COLLECTION_MEDIA` | Get Collection Media | Tool to get all media within a collection by its ID. Use when you need to fetch paginated media from a specific collection. |
| `PEXELS_CURATED_PHOTOS` | Get Curated Photos | Tool to get real-time curated photos. Use when you need to fetch curated photos with pagination support. |
| `PEXELS_FEATURED_COLLECTIONS` | Featured Collections | Tool to get featured collections. Use when you need curated collections of photos and videos with pagination support. |
| `PEXELS_GET_PHOTO` | Get Photo | Tool to retrieve detailed information about a specific photo. Use when you have a valid photo ID to fetch metadata including dimensions, photographer details, and image URLs. Use after confirming the photo ID from search or curated endpoints. |
| `PEXELS_GET_VIDEO_BY_ID` | Get Video by ID | Tool to retrieve detailed information about a specific video from Pexels. Use when you have a valid video ID to fetch metadata including dimensions, duration, videographer details, and available video file versions. |
| `PEXELS_MY_COLLECTIONS` | Get My Collections | Tool to get all of the user's collections on Pexels. Use when you need to list a user's collections with pagination support. |
| `PEXELS_POPULAR_VIDEOS` | Get Popular Videos | Tool to retrieve current popular Pexels videos. Use when you want to fetch trending videos from Pexels. |
| `PEXELS_SEARCH_PHOTOS` | Search Photos | Tool to search for photos on Pexels. Use when you need to retrieve photos by a search term and optional filters. Call after confirming you have a valid Pexels API key. Response image URLs are nested under `photo.src.` (e.g., `photo.src.original`, `photo.src.landscape`, `photo.src.medium`); the top-level `url` field is not sufficient for accessing specific image sizes. |
| `PEXELS_SEARCH_VIDEOS` | Search Videos | Tool to search for videos on Pexels by query and optional filters. Use when you need to find relevant video assets. Combining multiple filters with a narrow query may return few or no results; only apply strict filter combinations when explicitly required. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Pexels MCP server is an implementation of the Model Context Protocol that connects your AI agent to Pexels. It provides structured and secure access so your agent can perform Pexels operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Pexels project
- Some knowledge of Python or Typescript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Pexels.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only pexels.
- The router checks the user's Pexels connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Pexels.
- This approach keeps things lightweight and lets the agent request Pexels tools only when needed during the conversation.
```python
# Create a Pexels Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["pexels"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Pexels
const session = await composio.create(userId as string, {
  toolkits: ['pexels'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Pexels. "
        "Help users perform Pexels operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Pexels. Help users perform Pexels operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["pexels"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Pexels. "
        "Help users perform Pexels operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['pexels'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Pexels. Help users perform Pexels operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating Pexels MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Pexels.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Pexels MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/pexels/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/pexels/framework/antigravity)
- [Claude Agent SDK](https://composio.dev/toolkits/pexels/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/pexels/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/pexels/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/pexels/framework/codex)
- [Cursor](https://composio.dev/toolkits/pexels/framework/cursor)
- [VS Code](https://composio.dev/toolkits/pexels/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/pexels/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/pexels/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/pexels/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/pexels/framework/cli)
- [Google ADK](https://composio.dev/toolkits/pexels/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/pexels/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/pexels/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/pexels/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/pexels/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/pexels/framework/crew-ai)

## Related Toolkits

- [Figma](https://composio.dev/toolkits/figma) - Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing.
- [Abyssale](https://composio.dev/toolkits/abyssale) - Abyssale is a creative automation platform for generating images, videos, GIFs, PDFs, and HTML5 content programmatically. It streamlines and scales visual content production for marketing, design, and operations teams.
- [Alttext ai](https://composio.dev/toolkits/alttext_ai) - AltText.ai is a service that generates alt text for images automatically. It helps boost accessibility and SEO for your visual content.
- [Bannerbear](https://composio.dev/toolkits/bannerbear) - Bannerbear is an API-driven platform for generating images and videos automatically at scale. It helps businesses create custom graphics, social visuals, and marketing assets using powerful templates.
- [Canva](https://composio.dev/toolkits/canva) - Canva is a drag-and-drop design suite for creating professional graphics, presentations, and marketing materials. It makes it easy for anyone to design with beautiful templates and a vast library of elements.
- [Claid ai](https://composio.dev/toolkits/claid_ai) - Claid.ai delivers AI-driven image editing APIs for tasks like background removal, upscaling, and color correction. It helps automate and enhance image workflows with powerful, developer-friendly tools.
- [Cloudinary](https://composio.dev/toolkits/cloudinary) - Cloudinary is a cloud-based platform for managing, uploading, and transforming images and videos. It streamlines media workflows and delivers optimized assets globally.
- [Cults](https://composio.dev/toolkits/cults) - Cults is a digital marketplace for 3D printing models, connecting designers and makers. It lets creators share, sell, and discover a huge variety of printable designs easily.
- [DeepImage](https://composio.dev/toolkits/deepimage) - DeepImage is an AI-powered image enhancer and upscaler. Get higher-quality images with just a few clicks.
- [Dreamstudio](https://composio.dev/toolkits/dreamstudio) - DreamStudio is Stability AI’s platform for generating and editing images with AI. It lets you easily turn ideas into stunning visuals, fast.
- [Dynapictures](https://composio.dev/toolkits/dynapictures) - Dynapictures is a cloud-based platform for generating personalized images at scale. Instantly create hundreds of custom visuals using your data sources, like Google Sheets.
- [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools.
- [Gamma](https://composio.dev/toolkits/gamma) - Gamma is an AI-powered platform for making beautiful, interactive presentations and documents. It lets anyone create and share engaging decks with minimal effort.
- [Html to image](https://composio.dev/toolkits/html_to_image) - Html to image converts HTML and CSS into images or captures web page screenshots. Instantly generate visuals from code or web content—no manual screenshots needed.
- [Imagior](https://composio.dev/toolkits/imagior) - Imagior is an AI-powered image generation platform that lets you create and customize images using dynamic templates and APIs. Perfect for businesses and creators needing fast, scalable visuals without design hassle.
- [Imejis io](https://composio.dev/toolkits/imejis_io) - Imejis io is an API-based image generation platform with powerful customization and template support. It lets you create and modify images in seconds, no manual design work required.
- [Imgix](https://composio.dev/toolkits/imgix) - Imgix is a real-time image processing and delivery service for developers. It helps you optimize, transform, and deliver images efficiently at any scale.
- [Kraken io](https://composio.dev/toolkits/kraken_io) - Kraken.io is an image optimization and compression platform. It helps you shrink image file sizes while keeping visual quality intact.
- [Logo dev](https://composio.dev/toolkits/logo_dev) - Logo.dev is an API and database for high-resolution company logos and brand metadata. Instantly fetch official logos from any domain without scraping or manual searching.
- [Miro](https://composio.dev/toolkits/miro) - Miro is a collaborative online whiteboard platform for teams to brainstorm, design, and manage projects visually. It streamlines teamwork by enabling real-time idea sharing, diagramming, and workflow planning in a single space.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Pexels MCP?

With a standalone Pexels MCP server, the agents and LLMs can only access a fixed set of Pexels tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Pexels and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Pexels tools.

### Can I manage the permissions and scopes for Pexels while using Tool Router?

Yes, absolutely. You can configure which Pexels scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Pexels data and credentials are handled as safely as possible.

---
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