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 Pydantic AI 10 tools — connect in under 2 minutes

Name: Alchemer
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Alchemer through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Alchemer "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Alchemer?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

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IAMAccess control

EU AI ActCompliant

DLPData protection

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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 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.

Pydantic AI validates every Alchemer tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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.

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 Pydantic AI 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 Pydantic AI via MCP

Follow these steps to integrate the Alchemer MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Alchemer with type-safe schemas

Why Use Pydantic AI with the Alchemer MCP Server

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

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Alchemer integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Alchemer connection logic from agent behavior for testable, maintainable code

Alchemer + Pydantic AI Use Cases

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

Type-safe data pipelines: query Alchemer with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Alchemer tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Alchemer and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Alchemer responses and write comprehensive agent tests

Alchemer MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Alchemer to Pydantic AI 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 Pydantic AI

Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Alchemer + Pydantic AI FAQ

Common questions about integrating Alchemer MCP Server with Pydantic AI.

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 Alchemer MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.