Bring Customer Feedback
to CrewAI
Learn how to connect Refiner to CrewAI and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Refiner MCP Server?
Connect your Refiner customer feedback account to any AI agent and simplify how you collect in-product insights, manage user segments, and monitor survey performance through natural conversation.
What you can do
- Survey Oversight — List all in-app, email, and link surveys and retrieve detailed status and response counts.
- Response Analysis — Query survey submissions with technical filters like UUIDs and date ranges to identify trends.
- Identity & Targeting — Identify users and upsert technical traits to ensure surveys reach the right audience.
- Event-Driven Feedback — Track high-fidelity user actions programmatically to trigger perfectly timed micro-surveys via AI.
- Segment Intelligence — List and query defined user segments to understand your audience distribution.
- Operational Monitoring — Check API health and verify account configurations directly from the agent.
How it works
1. Subscribe to this server
2. Enter your Refiner API Key (found in your project settings)
3. Start managing your feedback ecosystem from Claude, Cursor, or any MCP client
Who is this for?
- Product Managers — quickly check survey results and user sentiment via simple AI commands.
- Growth & Marketing — automate event tracking and verify segment metadata directly from the workspace.
- Customer Success — monitor individual user feedback and verify identity traits via the AI assistant.
Built-in capabilities (8)
Check API Status
Get contact details
Identify or update user
List product contacts
List survey responses
List user segments
List feedback surveys
Track user event
Why CrewAI?
When paired with CrewAI, Refiner becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Refiner tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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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
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter 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
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Refiner in CrewAI
Refiner and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Refiner to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Refiner in CrewAI
The Refiner 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. All 8 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Refiner for CrewAI
Every tool call from CrewAI to the Refiner MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I check the responses for a specific survey via AI?
Yes! Use the list_refiner_responses tool and provide the Survey UUID. Your agent will retrieve the latest submissions, which you can then ask the AI to summarize or filter by date.
How do I identify a user and add custom traits using the agent?
Use the identify_refiner_user action. Provide the User ID or Email and a JSON string of traits (e.g., '{"plan":"pro"}'). This helps you target surveys based on specific user metadata.
Is it possible to track a custom event to trigger a survey via AI?
Absolutely. Use the track_refiner_event tool. Provide the event name and the user's ID/Email. When this event is logged, Refiner will trigger any surveys you have configured for that specific action.
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.
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.