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Using CrewAI with DataDoe MCP

CrewAI (opens in a new tab) is an open-source platform for orchestrating AI agent teams and building automatic workflows. It supports connecting source code, GitHub repositories, custom MCP servers, and prompt-driven workflow creation.

In this setup, DataDoe MCP acts as the data layer for agents created in CrewAI. Your automations call DataDoe tools to read live Amazon Seller, Vendor, and Ads data — similar to scheduled tasks or automations you might run in Claude Code, but managed inside the CrewAI platform.

What you will build

By the end of this tutorial, you will have a CrewAI automation that:

  • Discovers all Amazon seller accounts linked to your DataDoe organization
  • For each seller, generates a 7-day sales report with a daily breakdown and totals
  • Returns a consolidated markdown report combining all sellers
  • Can be run on demand or on a schedule inside CrewAI AMP (opens in a new tab)

This walkthrough uses CrewAI's built-in free LLM — no external API key is required to follow along.

Prerequisites

Step 1: Create a CrewAI account

  1. Go to app.crewai.com (opens in a new tab) and sign up.
  2. Complete onboarding and verify your email if prompted.

Step 2: Add DataDoe as a custom MCP server

Follow the CrewAI custom MCP server documentation (opens in a new tab):

  1. Open Tools & Integrations → Connections.
  2. Click Add Connection.
  3. Fill in:
    • Name: DataDoe (or any descriptive label)
    • Description: optional — e.g. "Amazon seller data via DataDoe MCP"
    • Server URL: https://mcp.datadoe.com/mcp/v1
  4. Choose Authentication Token as the authentication method:
  5. Click Create MCP Server and confirm DataDoe tools appear in Connections.

Quick setup reference

If you already know CrewAI, here is everything you need:

URL:     https://mcp.datadoe.com/mcp/v1
Auth:    Authentication Token
Header:  datadoe-mcp-key
Value:   <YOUR_DATADOE_MCP_KEY>

Step 3: Create the automation with a prompt

  1. In CrewAI Automations module, start a new automation using the prompt-based flow creator Crew Studio — do not pick a pre-built template.
  2. Paste the automation prompt below.
  3. Confirm DataDoe MCP tools are available to the agents in this flow.

Create automation using DataDoe MCP, which prepares Sales Raport for last 7 days for my each available Amazon seller. For each seller, report should cover:
- Daily profit and cost breakdown per SKU and child ASIN
- Base calculations on shipped orders, settlement fees, COGS, and ads spend
- Show data for the last 7 days only
- Show top 5 most profitable products for the same period
Use the relevant columns from report such as:
  - child_asin
  - sku
  - profit
  - total_cost
  - acos
  - tacos
  - roi
  - total_sales
  - total_units_sold
  - total_items
Choose a sensible executive KPI set for the top section, focused on profitability and business performance for the 7-day period

Goal: this report helps the user understand daily profitability and cost structure.

Data source:
- Use DataDoe
- Use the table: Profit by SKU & Date
- Seller: all available on my account
- Time period: last 7 days

Step 4: Review the generated automation

After CrewAI processes your prompt, it scaffolds a visual workflow with agents, tasks, and an optional trigger block.

You should see three agents, three tasks, and a Triggers block you can configure later for scheduling.

Step 5: Understand the main blocks

The automation diagram shows how data flows from DataDoe through analysis to the final report.

Triggers

BlockRole
TriggersStarts the automation manually, on a schedule, or on an event. Initially shows "No triggers configured" — you can add Event or Schedule triggers later.

Agents

BlockRole
Amazon Sales Data AnalystRetrieves and organizes sales data from DataDoe for all connected Amazon sellers. Has DataDoe MCP attached as a tool — this is the agent that calls your live Amazon data.
Business Intelligence AnalystProcesses and analyzes the collected sales data to generate key performance insights and executive KPIs for the 7-day window.
Executive Report WriterCreates the final comprehensive, well-structured consolidated sales report in markdown format.

Tasks

BlockRole
Collect Seller DataRetrieve all connected Amazon sellers from DataDoe and gather their 7-day profit data from the Profit by SKU & Date table. Feeds into the analysis and report tasks.
Analyze Performance MetricsProcess the collected sales data to calculate comprehensive executive KPIs and performance insights (e.g. total 7-day sales, units, profit trends).
Generate Consolidated ReportCombine all sellers' data into one professional markdown report with per-seller sections, daily breakdowns, and summary totals.

Flow: Trigger → Collect Seller Data (via Amazon Sales Data Analyst + DataDoe MCP) → Analyze Performance Metrics (via Business Intelligence Analyst) → Generate Consolidated Report (via Executive Report Writer).

Step 6: Configure LLM models on agent blocks

Each agent block can use a different LLM model:

  • CrewAI provides some models for free on the built-in account — this tutorial uses a free built-in model so no extra setup is required.
  • Premium models (e.g. gpt-5.4-mini and other OpenAI models) require you to add your own OPENAI_API_KEY in CrewAI settings.

The example diagram may show gpt-5.4-mini on agents — that requires an OpenAI API key. For this tutorial walkthrough, switch each agent to a free built-in CrewAI model instead.

Open the model picker on each agent block to change the model:

Step 7: Run the automation and review results

  1. Click Run (or Test) on the automation.
  2. Wait for DataDoe MCP tool calls to complete.
  3. Review the output panel.

Related resources

DataDoe MCP resources

Check the following resources for more information: