How do I obtain my Fairing API Key?

You can find your API Key in the Fairing admin portal under **Settings > Account**. Note that API access may depend on your current subscription plan.

Can I see responses for a specific customer?

Yes! Use the `get_customer_responses` tool with the specific Customer ID to retrieve all survey feedback associated with that individual.

What kind of insights can I extract?

The `get_insights` tool provides aggregated data on question performance, response rates, and attribution trends across your survey streams.

Fairing MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Fairing
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Fairing through Vinkius, pass the Edge URL in the `mcps` parameter and every Fairing 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="Fairing Specialist",
    goal="Help users interact with Fairing effectively",
    backstory=(
        "You are an expert at leveraging Fairing 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 Fairing "
        "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 Fairing MCP Server

Connect your Fairing (formerly EnquireLabs) account to any AI agent and take full control of your post-purchase surveys and zero-party data through natural conversation.

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

Survey & Question Management — List all active questions and fetch detailed configurations for your post-purchase surveys
Response Tracking — List and inspect individual survey responses to understand customer sentiment and attribution
Zero-Party Data Analysis — Query customer-specific responses to pair survey data with your marketing profiles
Aggregated Insights — Extract high-level insights and performance metrics across all your survey streams
Integration Audit — Monitor active integrations with platforms like Klaviyo, GA4, and Meta directly from the cloud
Account Context — Retrieve your Fairing account details and API token identity flawlessly

The Fairing 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 Fairing to CrewAI via MCP

Follow these steps to integrate the Fairing 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 Fairing

Why Use CrewAI with the Fairing MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Fairing 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

Fairing + CrewAI Use Cases

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

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

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

Fairing MCP Tools for CrewAI (12)

These 12 tools become available when you connect Fairing to CrewAI via MCP:

get_account_info

Get Fairing account information

get_customer_responses

Get all survey responses for a specific customer

get_insights

Get aggregated survey insights

get_me

Get current API token identity

get_question

Get details for a specific survey question

get_response

Get details for a specific survey response

get_survey_details

Get details for a specific survey

list_customers

List customers who have interacted with surveys

list_integrations

List active Fairing integrations

list_questions

List all Fairing survey questions

list_responses

List all survey responses

list_surveys

List all Fairing surveys

Example Prompts for Fairing in CrewAI

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

"List all active survey questions on Fairing."

"Show me the latest 5 survey responses."

"Check my active integrations on Fairing."

Troubleshooting Fairing MCP Server with CrewAI

Common issues when connecting Fairing 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.

Fairing + CrewAI FAQ

Common questions about integrating Fairing 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.