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 CrewAI 10 tools — connect in under 2 minutes

Name: Alchemer
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Alchemer through Vinkius, pass the Edge URL in the `mcps` parameter and every Alchemer tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Alchemer Specialist",
    goal="Help users interact with Alchemer effectively",
    backstory=(
        "You are an expert at leveraging Alchemer tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Alchemer "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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.

When paired with CrewAI, Alchemer becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Alchemer tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Alchemer MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Alchemer

Why Use CrewAI with the Alchemer MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Alchemer through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Alchemer + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Alchemer for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Alchemer, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Alchemer tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Alchemer against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Alchemer MCP Tools for CrewAI (10)

These 10 tools become available when you connect Alchemer to CrewAI 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 CrewAI

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

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Alchemer + CrewAI FAQ

Common questions about integrating Alchemer MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.