How do I find my Amazon DSP API credentials?

You need to create a 'Login with Amazon' application in the Amazon Developer Console to get your Client ID and Client Secret. Then, you generate a Refresh Token. You also need your Advertiser ID.

How do I choose the correct region?

Select the region that matches your target marketplace: **NA** (North America - US, CA, MX, BR), **EU** (Europe - UK, DE, FR, IT, ES, etc.), or **FE** (Far East - JP, AU, SG).

Why do reports take time to generate?

Amazon Ads reporting API is asynchronous. When you request a report, it returns a `reportId`. You must wait a few moments and use the check status tool to download the data once it's ready.

Amazon DSP MCP Server for CrewAI 7 tools — connect in under 2 minutes

Name: Amazon DSP
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 7 Tools Framework

Connect your CrewAI agents to Amazon DSP through Vinkius, pass the Edge URL in the `mcps` parameter and every Amazon DSP tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Amazon DSP Specialist",
    goal="Help users interact with Amazon DSP effectively",
    backstory=(
        "You are an expert at leveraging Amazon DSP tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Amazon DSP "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 7 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Amazon DSP MCP Server

Connect your Amazon DSP (Demand-Side Platform) account to your AI agent to unlock professional programmatic advertising orchestration. From managing display and video campaigns to auditing audience segments and tracking performance reports, your agent handles your programmatic strategy through natural conversation.

When paired with CrewAI, Amazon DSP becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Amazon DSP tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Campaign Orchestration — List and manage DSP campaigns (formerly Orders) and monitor their budgets and delivery statuses
Ad Group Oversight — Retrieve details for ad groups (Line Items) to verify targeting and pacing settings
Creative Management — List and audit creative assets associated with your campaigns to ensure brand compliance
Audience Targeting — Retrieve custom audiences and segments used for precise programmatic targeting
Performance Reporting — Request and monitor asynchronous performance reports to analyze impressions, reach, and conversions

The Amazon DSP MCP Server exposes 7 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Amazon DSP to CrewAI via MCP

Follow these steps to integrate the Amazon DSP MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 7 tools from Amazon DSP

Why Use CrewAI with the Amazon DSP MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Amazon DSP through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Amazon DSP + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Amazon DSP MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Amazon DSP for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Amazon DSP, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Amazon DSP tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Amazon DSP against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Amazon DSP MCP Tools for CrewAI (7)

These 7 tools become available when you connect Amazon DSP to CrewAI via MCP:

get_campaign_details

Get campaign metadata

get_report_status

Check report status

list_ad_groups

List DSP ad groups

list_audiences

List audiences

list_campaigns

List DSP campaigns

list_creatives

List creatives

request_report

Request performance report

Example Prompts for Amazon DSP in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Amazon DSP immediately.

"List my Amazon DSP campaigns."

"Show me the active ad groups for campaign ID '123456'."

"Request a DSP performance report for yesterday."

Troubleshooting Amazon DSP MCP Server with CrewAI

Common issues when connecting Amazon DSP to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Amazon DSP + CrewAI FAQ

Common questions about integrating Amazon DSP MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.