Bring Visual Feedback
to CrewAI
Learn how to connect Userback to CrewAI and start using 6 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Userback MCP Server?
Connect your Userback account to any AI agent and simplify how you collect and manage visual feedback, bug reports, and user suggestions through natural conversation.
What you can do
- Feedback Management — List all feedback entries and retrieve detailed metadata, screenshots, and comments for specific reports.
- Project Control — List and query feedback projects to keep your development and design work organized.
- Direct Creation — Programmatically create new feedback entries or bug reports for specific projects via AI.
- Team Visibility — List account users and collaborators to understand your organization's review team.
- Status Tracking — Monitor the progress of feedback items and verify if issues have been resolved.
How it works
1. Subscribe to this server
2. Enter your Userback API Token (found in your account settings under API)
3. Start managing your visual feedback from Claude, Cursor, or any MCP client
Who is this for?
- Product Managers & Designers — quickly retrieve user feedback and verify visual bugs via simple AI commands.
- QA & Support Teams — monitor incoming reports and create feedback entries directly from the workspace.
- Development Leads — coordinate bug fixes and track feedback status across multiple projects.
Built-in capabilities (6)
Create a new feedback entry
Get details for a specific feedback
Get details for a specific project
List account users
List Userback feedbacks
List Userback projects
Why CrewAI?
When paired with CrewAI, Userback becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Userback 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
Userback in CrewAI
Userback and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Userback 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 Userback in CrewAI
The Userback 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 6 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
Userback for CrewAI
Every tool call from CrewAI to the Userback MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I filter feedback by project ID?
Yes! Use the list_feedbacks tool and provide the optional project_id parameter to retrieve entries only for that specific project.
How do I see the comments on a specific feedback item?
Run the get_feedback_details query with the unique Feedback ID. Your agent will retrieve the complete metadata, including any internal or user comments.
Is it possible to create a new bug report via AI?
Absolutely. Use the create_feedback_entry action. Provide the Project ID, a title, and an optional comment to log a new entry in your Userback account.
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.