3,400+ MCP servers ready to use
Vinkius

Bring Visual Feedback
to LangChain

Learn how to connect Userback to LangChain and start using 6 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

Create Feedback EntryGet Feedback DetailsGet Project DetailsList Account UsersList FeedbacksList Userback Projects

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_feedback_entry

Create a new feedback entry

get_feedback_details

Get details for a specific feedback

get_project_details

Get details for a specific project

list_account_users

List account users

list_feedbacks

List Userback feedbacks

list_userback_projects

List Userback projects

Why LangChain?

LangChain's ecosystem of 500+ components combines seamlessly with Userback through native MCP adapters. Connect 6 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

  • The largest ecosystem of integrations, chains, and agents. combine Userback MCP tools with 500+ LangChain components

  • Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

  • LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

  • Memory and conversation persistence let agents maintain context across Userback queries for multi-turn workflows

See it in action

Userback in LangChain

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Why Vinkius

Userback and 3,400+ other MCP servers. One platform. One governance layer.

Teams that connect Userback to LangChain 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.

3,400+MCP Servers ready
<40msCold start
60%Token savings
Raw MCP
Vinkius
Server catalogFind and host yourself3,400+ managed
InfrastructureSelf-hostedSandboxed V8 isolates
Credential handlingPlaintext in configVault + runtime injection
Data loss preventionNoneConfigurable DLP policies
Kill switchNoneGlobal instant shutdown
Financial circuit breakersNonePer-server limits + alerts
Audit trailNoneEd25519 signed logs
SIEM log streamingNoneSplunk, Datadog, Webhook
HoneytokensNoneCanary alerts on leak
Custom domainsNot applicableDNS challenge verified
GDPR complianceManual effortAutomated purge + export
Enterprise Security

Why teams choose Vinkius for Userback in LangChain

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 LangChain 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.

Userback
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

The Vinkius Advantage

How Vinkius secures Userback for LangChain

Every tool call from LangChain to the Userback MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start
Ed25519Signed audit chain
60%Token savings
FAQ

Frequently asked questions

01

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.

02

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.

03

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.

04

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

05

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.

06

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

07

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters