How do I find my Alchemer API Token and Secret?

Log in to Alchemer as an admin, navigate to **Account** > **Integrations** > **API Access**. You can generate and copy your `api_token` and `api_token_secret` there.

Which region should I choose?

Choose the region based on your account's data center: **US** (api.alchemer.com), **EU** (api.alchemer.eu), or **CA** (api.alchemer.ca).

Can I retrieve responses for a specific survey?

Yes! Use the `list_survey_responses` tool and provide the Survey ID. Your agent will retrieve the latest submissions, including timestamps and completion status.

Alchemer MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Alchemer
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Alchemer 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({
        "alchemer": {
            "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 Alchemer, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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

About Alchemer MCP Server

Connect your Alchemer (formerly SurveyGizmo) account to your AI agent to unlock professional survey management and customer feedback orchestration. From auditing survey structures and questions to retrieving real-time responses and generating granular reports, your agent handles your feedback lifecycle through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Alchemer through native MCP adapters. Connect 10 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.

What you can do

Survey Orchestration — List and retrieve details for surveys, including their current status and technical metadata
Question Management — List and audit survey questions to ensure your data collection is precisely configured
Response Auditing — Retrieve and analyze individual or aggregated survey responses directly from chat
Reporting & Campaigns — List and manage survey reports and campaigns to monitor your data distribution and analysis
Contact Oversight — List and manage contact lists used for targeted survey distribution

The Alchemer MCP Server exposes 10 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 Alchemer to LangChain via MCP

Follow these steps to integrate the Alchemer 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 10 tools from Alchemer via MCP

Why Use LangChain with the Alchemer MCP Server

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

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

Alchemer + LangChain Use Cases

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

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

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

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

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

Alchemer MCP Tools for LangChain (10)

These 10 tools become available when you connect Alchemer to LangChain via MCP:

get_account_usage

Check account status

get_question_details

Get question metadata

get_response_details

Get response data

get_survey_details

Get survey metadata

list_contact_lists

List survey contacts

list_survey_campaigns

List distribution campaigns

list_survey_questions

List survey questions

list_survey_reports

List survey reports

list_survey_responses

List survey submissions

list_surveys

List account surveys

Example Prompts for Alchemer in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Alchemer immediately.

"List all active surveys in my Alchemer account."

"Show me the last 5 responses for survey ID 1234567."

"List all questions in the 'Customer Satisfaction' survey."

Troubleshooting Alchemer MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Alchemer + LangChain FAQ

Common questions about integrating Alchemer 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.