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 LangChain 12 tools — connect in under 2 minutes

Name: GetFeedback
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect GetFeedback through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "getfeedback": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using GetFeedback, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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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

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.

LangChain's ecosystem of 500+ components combines seamlessly with GetFeedback through native MCP adapters. Connect 12 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.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the GetFeedback MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 12 tools from GetFeedback via MCP

Why Use LangChain with the GetFeedback MCP Server

LangChain provides unique advantages when paired with GetFeedback through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine GetFeedback 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 GetFeedback queries for multi-turn workflows

GetFeedback + LangChain Use Cases

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

RAG with live data: combine GetFeedback tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query GetFeedback, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain GetFeedback tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every GetFeedback tool call, measure latency, and optimize your agent's performance

GetFeedback MCP Tools for LangChain (12)

These 12 tools become available when you connect GetFeedback to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

Common issues when connecting GetFeedback to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

GetFeedback + LangChain FAQ

Common questions about integrating GetFeedback MCP Server with LangChain.

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.

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.