# Adobe Marketing Agent MCP

```json
{
  "name": "Adobe Marketing Agent MCP",
  "slug": "adobe_marketing_agent_mcp",
  "url": "https://composio.dev/toolkits/adobe_marketing_agent_mcp",
  "markdown_url": "https://composio.dev/toolkits/adobe_marketing_agent_mcp.md",
  "logo_url": "https://logos.composio.dev/api/adobe_marketing_agent_mcp",
  "categories": [
    "marketing & social media"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-09-01T05:31:30.508Z"
}
```

![Adobe Marketing Agent MCP logo](https://logos.composio.dev/api/adobe_marketing_agent_mcp)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Adobe Marketing Agent MCP or direct API to retrieve campaign metrics, update audience segments, create promotional messages, and apply marketing preferences through natural language.

## Summary

Adobe Marketing Agent MCP is Adobe's hosted MCP service that exposes marketing context, preferences, and agent capabilities.
Use it to provide agents with campaign, audience, and analytics context via a managed integration.

## Categories

- marketing & social media

## Toolkit Details

- Tools: 12

## Images

- Logo: https://logos.composio.dev/api/adobe_marketing_agent_mcp

## Authentication

- **Dcr Oauth**
  - Type: `custom`
  - Description: Dcr Oauth authentication for Adobe Marketing Agent MCP.
  - Setup:
    - Configure Dcr Oauth credentials for Adobe Marketing Agent MCP.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- Fetch campaign performance for last week
- Update audience segment based on purchases
- Create promotional email in Adobe Campaign

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ADOBE_MARKETING_AGENT_MCP_ADOBE_MARKETING_AGENT_MCP_WIDGET` | Adobe-marketing-agent-mcp-widget | This MCP server provides a comprehensive suite of capabilities for analyzing audience metrics, discovering relevant data fields, and gaining insights into product functionalities within the Adobe Experience Platform. Users can retrieve and analyze historical audience sizes and trends, identify anomalies, and explore relationships between various data entities. Additionally, the tool facilitates the discovery of XDM attributes, answers product-related queries, and generates visualizations for business metrics, enabling users to make informed decisions based on data-driven insights. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_CONTEXT_MANAGEMENT_WIDGET` | Core-context-management-widget | Interactive widget to view and manage user context. Use this to display current organization, sandbox, and dataview, and to allow the user to switch between them. Call this widget when the user wants to see their context, list available sandboxes, list available dataviews, list available organizations, change sandbox, change dataview, or switch organization. Note: Users refer to sandboxes by title (e.g. "Production"), not by name (e.g. "prod"). |
| `ADOBE_MARKETING_AGENT_MCP_CORE_FEEDBACK_WIDGET` | Core-feedback-widget | Call this widget when the user wants to provide feedback or rate their experience. This displays an interactive feedback form with thumbs up/down buttons and rating categories. Users can select sentiment (like/dislike) and provide additional comments. If widgets are not supported by the surface, the system will automatically fall back to text-based feedback using core-provide_feedback tool. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_GET_TASK` | Core-get task | Get task status and events for an async task. Use cursor to get only new events since last poll. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_LIST_TASKS` | Core-list tasks | List async tasks for a conversation context_id. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_PLAN_COMPLETION_DECISION` | Core-plan completion decision | Submit the user's final decision to complete or cancel a pending plan. Use this tool when the system has proposed a plan step that requires user confirmation before it can be executed — such as creating an audience, a journey, a campaign, or any other entity. This is the final step that completes the plan. ALWAYS use this tool when: - The system is waiting for the user's decision to proceed with a plan - The user provides an explicit approve or reject response to a pending proposal - User says "approve", "go ahead", "create it", "looks good", "confirm", "do it" - User says "reject", "cancel", "don't create it", "decline", "stop" Parameters: - decision (required): "approve" to confirm and execute the plan, "reject" to cancel it Returns the final orchestrator response confirming the plan was completed or cancelled. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_PROVIDE_FEEDBACK` | Core-provide feedback | Submit user feedback about their experience with the AI assistant. Accepts a query parameter with the user's feedback message. Automatically classifies sentiment and submits to the feedback API. Use core-feedback-widget instead if the user wants to see a feedback form. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_SET_DATAVIEW` | Core-set dataview | Set the current dataview context. Use this when the user wants to switch to a different dataview. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_SET_SANDBOX` | Core-set sandbox | Set the current sandbox context. Use this when the user wants to switch to a different sandbox. The response contains the displayValue (e.g., 'Prod - Production (VA7)') which should be used when talking to the user. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_SWITCH_ORG` | Core-switch org | Switch to a different organization by exchanging the current token. Provide the organization name or IMS Org ID. Use list_orgs to see available organizations first. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_SWITCH_SANDBOX_DATAVIEW` | Core-switch sandbox dataview | This core system tool updates the current sandbox and/or dataview context for the session. Parameters: - sandboxName (optional): Name of the sandbox to set as current context it's usually one word - dataviewName (optional): Name of the dataview to set as current context The tool will: 1. Fetch the ID for each provided name from Adobe APIs 2. Update the session store with the IDs 3. Return confirmation of what was updated Note: At least one parameter must be provided based on what you want to change (sandbox/dataview). Use list_dataviews or list_sandboxes to see available options first. |
| `ADOBE_MARKETING_AGENT_MCP_CORE_USER_PREFERENCES` | Core-user preferences | Read or clear the current user's persisted preferences (sandbox, dataview, org, region). Preferences persist for 90 days across sessions and surfaces. Set automatically when the user configures a sandbox or dataview. Parameters: - action (optional): "get" (default) to read, "clear" to delete Returns JSON with sandbox_name, sandbox_id, dataview_id, dataview_name, org_id, region, updated_at. Fields are null when not set. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK
```python
pip install composio_openai
```

```typescript
npm install @composio/openai
```

#### Path 1, Step 2: Initialize Composio and Create Tool Router Session

Import and initialize Composio client, then create a Tool Router session
```python
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
openai = OpenAI()
session = composio.create(user_id='your-user-id')
```

```typescript
import OpenAI from 'openai';
import { Composio } from '@composio/core';
import { OpenAIResponsesProvider } from '@composio/openai';

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');
```

#### Path 1, Step 3: Execute Adobe Marketing Agent MCP Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute Adobe Marketing Agent MCP actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'YOUR_SPECIFIC_PROMPT_HERE'
  }]
)
result = composio.provider.handle_tool_calls(
  response=response,
  user_id='your-user-id'
)
print(result)
```

```typescript
const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'YOUR_SPECIFIC_PROMPT_HERE'
  }],
});
const result = await composio.provider.handleToolCalls(
  'your-user-id',
  response.output
);
console.log(result);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK for Python or TypeScript
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
```

#### Path 2, Step 2: Initialize Client and Create Tool Router Session

Import and initialize the Composio client, then create a Tool Router session for Adobe Marketing Agent MCP
```python
from composio import Composio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

composio = Composio(api_key='your-composio-api-key')
session = composio.create(user_id='your-user-id')
url = session.mcp.url
```

```typescript
import { Composio } from '@composio/core';

const composio = new Composio({ apiKey: 'your-api-key' });
const session = await composio.create('your-user-id');
console.log(`Tool Router session created: ${session.mcp.url}`);
```

#### Path 2, Step 3: Connect to AI Agent

Use the MCP server with your AI agent (Anthropic Claude or Mastra)
```python
import asyncio

options = ClaudeAgentOptions(
    permission_mode='bypassPermissions',
    mcp_servers={
        'tool_router': {
            'type': 'http',
            'url': url,
            'headers': {
                'x-api-key': 'your-composio-api-key'
            }
        }
    },
    system_prompt='You are a helpful assistant with access to Adobe Marketing Agent MCP tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('YOUR_SPECIFIC_PROMPT_HERE')
        async for message in client.receive_response():
            if hasattr(message, 'content'):
                for block in message.content:
                    if hasattr(block, 'text'):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { openai } from '@ai-sdk/openai';
import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp';
import { generateText } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: session.mcp.url,
    headers: {
      'x-api-key': 'your-composio-api-key',
    },
  },
});

const tools = await client.tools();
const { text } = await generateText({
  model: openai('gpt-4o'),
  tools,
  messages: [{
    role: 'user',
    content: 'YOUR_SPECIFIC_PROMPT_HERE'
  }],
  maxSteps: 5,
});

console.log(`Agent: ${text}`);
```

## Why Use Composio?

### 1. AI Native Adobe Marketing Agent MCP Integration

- Supports both Adobe Marketing Agent MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable tool execution
- Rich coverage for reading, writing, and querying your Adobe Marketing Agent MCP data

### 2. Managed Auth

- Built-in OAuth handling with automatic token refresh and rotation
- Central place to manage, scope, and revoke Adobe Marketing Agent MCP access
- Per user and per environment credentials instead of hard-coded keys

### 3. Agent Optimized Design

- Tools are tuned using real error and success rates to improve reliability over time
- Comprehensive execution logs so you always know what ran, when, and on whose behalf

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Adobe Marketing Agent MCP
- Scoped, least privilege access to Adobe Marketing Agent MCP resources
- Full audit trail of agent actions to support review and compliance

## Use Adobe Marketing Agent MCP with any AI Agent Framework

Choose a framework you want to connect Adobe Marketing Agent MCP with:

- [ChatGPT Work](https://composio.dev/toolkits/adobe_marketing_agent_mcp/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/adobe_marketing_agent_mcp/framework/claude-cowork)
- [Hermes](https://composio.dev/toolkits/adobe_marketing_agent_mcp/framework/hermes-agent)

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## Frequently Asked Questions

### Do I need my own developer credentials to use Adobe Marketing Agent MCP with Composio?

Yes, Adobe Marketing Agent MCP requires you to configure your own Dcr Oauth credentials. Once set up, Composio handles secure credential storage and management for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

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