How to integrate Giphy MCP with Autogen

This guide walks you through connecting Giphy to AutoGen using the Composio tool router. By the end, you'll have a working Giphy agent that can find trending cat gifs for today, get sticker variations for smile emoji, list gifs in the 'reactions' category through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Giphy account through Composio's Giphy MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide walks you through connecting Giphy to AutoGen using the Composio tool router. By the end, you'll have a working Giphy agent that can find trending cat gifs for today, get sticker variations for smile emoji, list gifs in the 'reactions' category through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Giphy account through Composio's Giphy MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Giphy with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Giphy
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Giphy tools
  • Run a live chat loop where you ask the agent to perform Giphy operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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

The Giphy MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Giphy account. It provides structured and secure access to the world’s largest GIF and sticker library, so your agent can search for GIFs, fetch trending categories, retrieve GIF metadata, and even track analytics on user interactions automatically.

  • GIF and sticker search and retrieval: Instantly have your agent fetch GIFs and stickers by ID, category, or emoji for any topic or mood you need.
  • Browse trending categories and curated content: Let your agent pull the latest GIF categories and browse curated collections to suggest the perfect GIF for any occasion.
  • Access detailed GIF and sticker metadata: Retrieve comprehensive information about specific GIFs, stickers, or even groups of items by their unique IDs.
  • Emoji and sticker variation discovery: Explore emoji GIFs and their creative variations, making it easy to add fun reactions or flair to your app or chat.
  • User interaction analytics logging: Track and register when users view, click, or share GIFs, enabling smarter personalization and reporting within your workflows.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Giphy account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Giphy via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Giphy connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Giphy session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["giphy"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Giphy tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Giphy assistant agent with MCP tools
    agent = AssistantAgent(
        name="giphy_assistant",
        description="An AI assistant that helps with Giphy operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Giphy tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Giphy related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Giphy tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Giphy and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Giphy session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["giphy"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Giphy assistant agent with MCP tools
        agent = AssistantAgent(
            name="giphy_assistant",
            description="An AI assistant that helps with Giphy operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Giphy related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Giphy through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Giphy, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Giphy action and event your agent gets out of the box.

Giphy Analytics Register

Tool to register user interactions (view, click, send) with a GIF for analytics.

GIPHY Categories

Tool to fetch a list of GIF categories on GIPHY.

GIPHY: Get Category by ID

Tool to fetch metadata for a GIF category by its unique ID.

GIPHY: Category GIFs

Tool to fetch GIFs associated with a specific GIF category.

GIPHY Emoji

Tool to fetch GIPHY emoji GIF objects.

Emoji Variations

Tool to fetch variations for a specific emoji.

Get Content by ID

Tool to fetch content metadata by its unique ID.

Get Content by IDs

Tool to fetch metadata for multiple pieces of content (GIFs, Stickers, or Clips) by their IDs.

Giphy Get Random ID

Tool to generate a unique random ID from Giphy.

Giphy Random GIF

Tool to fetch a random GIF from Giphy.

Giphy Random Sticker

Tool to fetch a single random sticker.

GIPHY: Search Channels

Tool to search for GIPHY channels by query term.

GIPHY: Search GIFs

Tool to search GIPHY's GIF library.

GIPHY: Search Stickers

Tool to search GIPHY's sticker library.

GIPHY: Random Tag

Tool to fetch a single random tag from Giphy.

Get Related Tags

Tool to fetch tags related to a specified tag.

GIPHY: Tag Search

Tool to search GIPHY's tag library for autocomplete suggestions.

GIPHY Trending Tags

Tool to fetch the most popular search terms (tags) on GIPHY.

GIPHY Translate GIF

Tool to translate a term or phrase into a single GIF using GIPHY's special algorithm.

GIPHY Translate Sticker

Tool to translate a term or phrase into a single sticker using GIPHY’s translation algorithm.

GIPHY Trending GIFs

Tool to fetch trending GIFs from GIPHY.

Get Trending Stickers

Tool to fetch trending stickers.

Giphy Upload GIF

Tool to upload a GIF or video file to GIPHY.

FRAMEWORKS

How to build Giphy MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Giphy MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Giphy MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Giphy MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Giphy MCP with Claude Cowork

Codex logo

Codex

Use Giphy MCP with Codex

OpenClaw logo

OpenClaw

Use Giphy MCP with OpenClaw

Hermes logo

Hermes

Use Giphy MCP with Hermes

CLI logo

CLI

Use Giphy MCP with CLI

Google ADK logo

Google ADK

Use Giphy MCP with Google ADK

LangChain logo

LangChain

Use Giphy MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Giphy MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Giphy MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Giphy MCP with LlamaIndex

CrewAI logo

CrewAI

Use Giphy MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. Autogen 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 Giphy tools.

Yes, absolutely. You can configure which Giphy 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.

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 Giphy data and credentials are handled as safely as possible.

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