Where do I find my Global Company ID?

The easiest way is to log in to the Adobe Developer Console and check your project settings. Alternatively, once you have an access token, the `list_report_suites` tool will return your authorized company metadata.

Are reports returned in real-time?

Yes. Unlike older versions of the API, the v2.0 Reporting API is synchronous and returns the data directly in the request response, making it perfect for AI interactions.

Does this support complex breakdowns?

Yes, the `get_report` tool accepts a JSON payload that supports the full range of Adobe Analytics v2.0 reporting features, including nested breakdowns and metric filters.

Adobe Analytics MCP Server for CrewAI 5 tools — connect in under 2 minutes

Name: Adobe Analytics
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 5 Tools Framework

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

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Open in ChatGPT Open in Claude Open in Perplexity

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Adobe Analytics Specialist",
    goal="Help users interact with Adobe Analytics effectively",
    backstory=(
        "You are an expert at leveraging Adobe Analytics 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 Adobe Analytics "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 5 available tools "
        "and what they can do."
    ),
)

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

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Adobe Analytics MCP Server

Connect your Adobe Analytics account to your AI agent to unlock deep customer journey insights and real-time data orchestration. From retrieving complex reporting breakdowns to managing audience segments and auditing calculated metrics, your agent handles your enterprise analytics ecosystem through natural conversation.

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

What you can do

Enterprise Reporting — Retrieve synchronous reports with nested breakdowns and complex filters directly from chat
Component Discovery — List and audit all available metrics and dimensions for your specific report suites
Segment Management — List and retrieve details for audience segments to ensure your data is always relevant
Report Suite Oversight — Manage and list your report suites (collections) to maintain organizational control
Real-time Performance — Quickly identify traffic trends and engagement patterns without manual dashboard configuration

The Adobe Analytics MCP Server exposes 5 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 Adobe Analytics to CrewAI via MCP

Follow these steps to integrate the Adobe Analytics 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 5 tools from Adobe Analytics

Why Use CrewAI with the Adobe Analytics MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Adobe Analytics 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 the 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

Adobe Analytics + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Adobe Analytics MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Adobe Analytics 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 Adobe Analytics, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Adobe Analytics 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 Adobe Analytics against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Adobe Analytics MCP Tools for CrewAI (5)

These 5 tools become available when you connect Adobe Analytics to CrewAI via MCP:

get_dimensions

g. Page, Device Type) for a specific report suite ID. List dimensions for a report suite

get_metrics

List metrics for a report suite

get_report

0 JSON report request body. Retrieve an analytics report

list_report_suites

List available report suites

list_segments

List audience segments

Example Prompts for Adobe Analytics in CrewAI

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

"List all metrics available for report suite 'mycompany-prod'."

"Show me the top 5 pages by visits for yesterday."

"List all active segments in my Adobe Analytics account."

Troubleshooting Adobe Analytics MCP Server with CrewAI

Common issues when connecting Adobe Analytics 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

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

Adobe Analytics + CrewAI FAQ

Common questions about integrating Adobe Analytics 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.