How do I obtain my Fera.ai Private API Key?

Log in to your Fera.ai dashboard, navigate to **Configuration > API Keys**, and look for your 'Secret Key'. Do not share this key with anyone.

Can I see photos submitted by customers?

Yes! Use the `list_media` tool to retrieve all user-generated photos and videos submitted alongside reviews for your store.

Does this work with my Shopify store?

Absolutely. Fera.ai integrates deeply with Shopify. As long as you provide the API key for your Fera account, you can manage reviews for your Shopify-connected stores.

Fera.ai MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Fera.ai
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Fera.ai through Vinkius, pass the Edge URL in the `mcps` parameter and every Fera.ai 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="Fera.ai Specialist",
    goal="Help users interact with Fera.ai effectively",
    backstory=(
        "You are an expert at leveraging Fera.ai 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 Fera.ai "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 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 Fera.ai MCP Server

Connect your Fera.ai account to any AI agent and take full control of your customer reviews, ratings, and user-generated content (UGC) through natural conversation.

When paired with CrewAI, Fera.ai becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Fera.ai 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

Review Orchestration — List all customer reviews and fetch detailed sentiment metadata for specific feedback natively
Rating Intelligence — Query aggregated product ratings and review counts to analyze catalog performance flawlessly
UGC Monitoring — List and inspect customer-submitted photos and videos to manage your visual social proof natively
Customer Insights — Access detailed profiles of customers who have submitted feedback to personalize engagement synchronously
Multi-Store Management — List and query data across all stores managed under your partner or business account flawlessly
Integration Audit — Monitor active external integrations with platforms like Shopify, Wix, and BigCommerce directly from the cloud
Identity Context — Verify your API secret key identity and account subscription details through the agent flawlessly

The Fera.ai MCP Server exposes 12 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 Fera.ai to CrewAI via MCP

Follow these steps to integrate the Fera.ai 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 12 tools from Fera.ai

Why Use CrewAI with the Fera.ai MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Fera.ai 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

Fera.ai + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Fera.ai MCP Server delivers measurable value.

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

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

Fera.ai MCP Tools for CrewAI (12)

These 12 tools become available when you connect Fera.ai to CrewAI via MCP:

get_account_info

Get Fera account and subscription details

get_customer

Get details for a specific customer profile

get_me

Get current API token identity info

get_product_rating

Get aggregated rating and review count for a product

get_review

Get details for a specific review

list_customers

List customers who have submitted feedback

list_external_integrations

List active external integrations (Shopify, etc.)

list_media

List customer-submitted photos and videos (UGC)

list_products

List products being tracked by Fera

list_reviews

List all customer reviews for your store

list_site_content

List social proof content and widgets

list_stores

List stores managed under your account

Example Prompts for Fera.ai in CrewAI

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

"List the latest 5 reviews for my store."

"Show me the average rating for product SKU-123."

"Check my active integrations on Fera."

Troubleshooting Fera.ai MCP Server with CrewAI

Common issues when connecting Fera.ai 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.

Fera.ai + CrewAI FAQ

Common questions about integrating Fera.ai 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.