Bring Visual Feedback
to Pydantic AI
Learn how to connect Userback to Pydantic AI 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 Pydantic AI?
Pydantic AI validates every Userback tool response against typed schemas, catching data inconsistencies at build time. Connect 6 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Userback integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your Userback connection logic from agent behavior for testable, maintainable code
Userback in Pydantic AI
Userback and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Userback to Pydantic AI 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 Pydantic AI
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 Pydantic AI 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 Pydantic AI
Every tool call from Pydantic AI 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 Pydantic AI discover MCP tools?
Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
Does Pydantic AI validate MCP tool responses?
Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your Userback MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai