How to integrate Giphy MCP with CrewAI

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Introduction

This guide walks you through connecting Giphy to CrewAI 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, fetch metadata for gif by id through natural language commands.

This guide will help you understand how to give your CrewAI 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.

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Giphy connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Giphy
  • Build a conversational loop where your agent can execute Giphy operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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.

Supported Tools & Triggers

Tools
Giphy Analytics RegisterTool to register user interactions (view, click, send) with a GIF for analytics.
Emoji VariationsTool to fetch variations for a specific emoji.
Get GIF by IDTool to fetch GIF metadata by its unique ID.
Get GIFs by IDsTool to fetch metadata for multiple GIFs by their IDs.
Get Sticker by IDTool to fetch sticker metadata by its unique ID.
Get Stickers by IDsTool to fetch metadata for multiple stickers by their IDs.
GIPHY CategoriesTool to fetch a list of GIF categories on GIPHY.
GIPHY: Get Category by IDTool to fetch metadata for a GIF category by its unique ID.
GIPHY: Category GIFsTool to fetch GIFs associated with a specific GIF category.
GIPHY EmojiTool to fetch GIPHY emoji GIF objects.
Get Related TagsTool to fetch tags related to a specified tag.
GIPHY: Tag SearchTool to search GIPHY's tag library for autocomplete suggestions.
GIPHY Trending TagsTool to fetch the most popular search terms (tags) on GIPHY.
GIPHY Translate StickerTool to translate a term or phrase into a single sticker using GIPHY’s translation algorithm.
Get Trending StickersTool to fetch trending stickers.
Giphy Random GIFTool to fetch a random GIF from Giphy.
Giphy Random StickerTool to fetch a single random sticker.
GIPHY: Search GIFsTool to search GIPHY's GIF library.
GIPHY: Search StickersTool to search GIPHY's sticker library.
GIPHY: Random TagTool to fetch a single random tag from Giphy.
GIPHY Trending GIFsTool to fetch trending GIFs from GIPHY.
Giphy Upload GIFTool to upload a GIF or video file to GIPHY.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Giphy connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Giphy via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Giphy MCP URL

Create a Composio Tool Router session for Giphy

python
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:
  • You create a Giphy only session through Composio
  • Composio returns an MCP HTTP URL that exposes Giphy tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Giphy Assistant",
    goal="Help users interact with Giphy through natural language commands",
    backstory=(
        "You are an expert assistant with access to Giphy tools. "
        "You can perform various Giphy operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Giphy MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Giphy operations.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Giphy related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_giphy_agent.py

Complete Code

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

python
# file: crewai_giphy_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

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 LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Giphy assistant agent
    toolkit_agent = Agent(
        role="Giphy Assistant",
        goal="Help users interact with Giphy through natural language commands",
        backstory=(
            "You are an expert assistant with access to Giphy tools. "
            "You can perform various Giphy operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Giphy operations.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Giphy related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Giphy through Composio's Tool Router. The agent can perform Giphy operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Giphy MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Giphy MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Giphy MCP with Claude Agent SDK

Google ADK

Google ADK

Use Giphy MCP with Google ADK

LangChain

LangChain

Use Giphy MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Giphy MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Giphy MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Giphy MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Giphy MCP?

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.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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.

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

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.

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 Giphy data and credentials are handled as safely as possible.

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