How do I get an Access Token for GetFeedback?

Log in to GetFeedback, navigate to your account settings or profile, and look for the API section to generate your Personal Access Token.

Can I see incomplete survey responses?

Yes! The 'list_survey_responses' tool allows you to filter by status. You can view responses that were 'started' but not yet finished, as well as 'completed' ones.

How do I send a survey to a list of people?

Use the 'send_survey_invites' tool. Provide the Survey ID and a JSON array of email addresses to trigger the invitations instantly.

Is the data returned in real-time?

Yes, all feedback data retrieved through this MCP server is fetched directly from the GetFeedback Reporting API, providing you with the latest available records.

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

Name: GetFeedback
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to GetFeedback through Vinkius, pass the Edge URL in the `mcps` parameter and every GetFeedback 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

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="GetFeedback Specialist",
    goal="Help users interact with GetFeedback effectively",
    backstory=(
        "You are an expert at leveraging GetFeedback 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 GetFeedback "
        "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 GetFeedback MCP Server

Connect your GetFeedback account to any AI agent to automate your customer feedback and survey reporting workflows through the Model Context Protocol (MCP). GetFeedback is a powerful, mobile-friendly survey platform that helps brands collect and analyze customer sentiment in real-time. This MCP server enables you to retrieve survey results, monitor completion statuses, and trigger survey invitations directly through natural conversation.

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

Key Features

Survey Orchestration — List all active surveys in your account and fetch detailed structural metadata for each form.
Real-time Response Tracking — Retrieve customer feedback as it arrives, including detailed answer payloads and completion timestamps.
Advanced Filtering — List survey responses filtered by status (started, completed) or created after a specific date for targeted reporting.
Automated Invitations — Trigger survey emails to a list of recipients programmatically from your chat interface.
Identity Oversight — Access global profile information for the authenticated GetFeedback user to ensure correct account context.
Data Connectivity — Verify your API connection and account health to maintain seamless feedback loops.
Asynchronous Monitoring — Fetch high-level response counts and status metrics to track survey performance instantly.

The GetFeedback 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 GetFeedback to CrewAI via MCP

Follow these steps to integrate the GetFeedback 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 GetFeedback

Why Use CrewAI with the GetFeedback MCP Server

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

GetFeedback + CrewAI Use Cases

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

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

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

GetFeedback MCP Tools for CrewAI (12)

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

check_api_limits

Verify connectivity

get_my_identity

Get user identity

get_response_details

Get response metadata

get_survey_details

Get survey metadata

get_survey_stats

Get response count

list_completed_feedback

Filter for completed

list_feedback_page

Paginated responses

list_recent_feedback

Filter by date

list_survey_responses

List feedback data

list_surveys

List all surveys

send_survey_invites

Trigger survey email

verify_api_connection

Check connection

Example Prompts for GetFeedback in CrewAI

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

"List all active surveys in my GetFeedback account."

"Show me the last 5 completed responses for survey '12345'."

"Send the 'Onboarding Survey' (ID: 98765) to ['user1@test.com', 'user2@test.com']."

Troubleshooting GetFeedback MCP Server with CrewAI

Common issues when connecting GetFeedback 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.

GetFeedback + CrewAI FAQ

Common questions about integrating GetFeedback 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.