# How to integrate Storyblok MCP with CrewAI

```json
{
  "title": "How to integrate Storyblok MCP with CrewAI",
  "toolkit": "Storyblok",
  "toolkit_slug": "storyblok",
  "framework": "CrewAI",
  "framework_slug": "crew-ai",
  "url": "https://composio.dev/toolkits/storyblok/framework/crew-ai",
  "markdown_url": "https://composio.dev/toolkits/storyblok/framework/crew-ai.md",
  "updated_at": "2026-03-29T06:51:51.822Z"
}
```

## Introduction

This guide walks you through connecting Storyblok to CrewAI using the Composio tool router. By the end, you'll have a working Storyblok agent that can create a new blog post draft, list all unpublished blog posts, update page content for the homepage through natural language commands.
This guide will help you understand how to give your CrewAI agent real control over a Storyblok account through Composio's Storyblok MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Storyblok with

- [OpenAI Agents SDK](https://composio.dev/toolkits/storyblok/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/storyblok/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/storyblok/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/storyblok/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/storyblok/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/storyblok/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/storyblok/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/storyblok/framework/cli)
- [Google ADK](https://composio.dev/toolkits/storyblok/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/storyblok/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/storyblok/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/storyblok/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/storyblok/framework/llama-index)

## TL;DR

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

The Storyblok MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Storyblok account. It provides structured and secure access so your agent can perform Storyblok operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `STORYBLOK_FETCH_CONTENT_TYPE_ITEMS_GRAPHQL` | Fetch Content Type Items (GraphQL) | Fetch multiple stories/content items using Storyblok's GraphQL API with filtering and pagination. Use starts_with with language code prefix (e.g., 'es/*', 'hi/*') to retrieve translated content in specific languages. |
| `STORYBLOK_FETCH_GRAPHQL_CONTENT_ITEM` | Fetch GraphQL Content Item | Tool to fetch a single story in a specific language using Storyblok GraphQL API with field-level translations. For each content type (e.g., Page), Storyblok generates a ContentTypeItem field (e.g., PageItem). Use when you need to retrieve a specific story by ID or slug with optional language translation. |
| `STORYBLOK_GET_APP` | Get Extension/App | Tool to retrieve a Storyblok extension/app by ID using the Management API. Use when you need to fetch details about a specific extension or app installed in Storyblok. |
| `STORYBLOK_GET_DATASOURCE_ENTRIES` | Get Datasource Entries | Tool to retrieve datasource entries from Storyblok via GraphQL API. Use when you need to fetch datasource data. Returns datasource entries with fields like id, name, value, and dimension_value. |
| `STORYBLOK_GET_GRAPHQL_RATE_LIMIT` | Get GraphQL Rate Limit | Tool to retrieve rate limit information from Storyblok GraphQL API. Use when you need to check the maximum cost per request to calculate safe request rates (100 / maxCost = requests per second). |
| `STORYBLOK_GET_PAGE_ITEM` | Get Page Item | Tool to retrieve a single page item by ID or slug from Storyblok using GraphQL. Use when you need to fetch specific page content with custom field selection. Supports both draft and published versions. |
| `STORYBLOK_LIST_GRAPHQL_CONTENT_TYPE_ITEMS` | List GraphQL Content Type Items | Tool to retrieve multiple content items with pagination, filtering, and relation resolution for any Storyblok content type via GraphQL. Content types are dynamically generated as [ContentType]Items (e.g., PageItems, BlogArticleItems). Use when you need to query structured content with flexible field selection and filtering. |
| `STORYBLOK_QUERY_PAGE_ITEMS_VIA_GRAPHQL` | Query page items via GraphQL | Execute GraphQL queries to retrieve multiple page items from Storyblok with filtering options. Use when you need to fetch page content with filters like path prefix, publish date, or slug exclusions. |
| `STORYBLOK_RETRIEVE_LINKS_VIA_GRAPHQL` | Retrieve Links via GraphQL | Tool to retrieve links for navigation using Storyblok's GraphQL API. Use when you need to fetch navigation links with their metadata (id, uuid, slug, name, published status). |
| `STORYBLOK_RETRIEVE_TAGS_VIA_GRAPHQL` | Retrieve Tags via GraphQL | Tool to retrieve tags from Storyblok via GraphQL API. Use when you need to fetch available tags for content organization and filtering. |

## Supported Triggers

None listed.

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

The Storyblok MCP server is an implementation of the Model Context Protocol that connects your AI agent to Storyblok. It provides structured and secure access so your agent can perform Storyblok 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:
- Python 3.9 or higher
- A Composio account and API key
- A Storyblok connection authorized in Composio
- An OpenAI API key for the CrewAI LLM
- Basic familiarity with Python

### 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).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

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

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

**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 Storyblok MCP URL
```python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
```

### 5. Create a Composio Tool Router session for Storyblok

**What's happening:**
- You create a Storyblok only session through Composio
- Composio returns an MCP HTTP URL that exposes Storyblok tools
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["storyblok"])

url = session.mcp.url
```

### 6. Initialize the MCP Server

**What's Happening:**
- Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
- MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
- Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
- Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
- Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
```python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
```

### 7. Create a CLI Chatloop and define the Crew

**What's Happening:**
- Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
- Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
- Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
- Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
- Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
- Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.
```python
print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

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

## Complete Code

```python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["storyblok"],
)
url = session.mcp.url

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

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

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

## Conclusion

You now have a CrewAI agent connected to Storyblok through Composio's Tool Router. The agent can perform Storyblok 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 Storyblok MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/storyblok/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/storyblok/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/storyblok/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/storyblok/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/storyblok/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/storyblok/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/storyblok/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/storyblok/framework/cli)
- [Google ADK](https://composio.dev/toolkits/storyblok/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/storyblok/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/storyblok/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/storyblok/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/storyblok/framework/llama-index)

## Related Toolkits

- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze.
- [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing.
- [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages.
- [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections.
- [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach.
- [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Affinda](https://composio.dev/toolkits/affinda) - Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.

## Frequently Asked Questions

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

With a standalone Storyblok MCP server, the agents and LLMs can only access a fixed set of Storyblok tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Storyblok 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 Storyblok tools.

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

Yes, absolutely. You can configure which Storyblok 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 Storyblok data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
