How do I find my Wenjuanxing App ID and Key?

Log in to your Wenjuanxing account (Enterprise/Flagship version), go to the Open API Platform (openapi.wjx.cn) or check the 'API/SSO' section in your user settings to find your App ID and Key.

Can I see quantitative statistics for survey questions?

Yes. Use the `get_stats` tool with your activity ID to retrieve counts and percentages for each answer option in your survey.

Is it possible to search questionnaires by keyword?

Yes! You can use the `query_surveys` tool to find specific questionnaires in your account based on their title or activity keyword.

Wenjuanxing / 问卷星 MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Wenjuanxing / 问卷星
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Wenjuanxing / 问卷星 Specialist",
    goal="Help users interact with Wenjuanxing / 问卷星 effectively",
    backstory=(
        "You are an expert at leveraging Wenjuanxing / 问卷星 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 Wenjuanxing / 问卷星 "
        "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)

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About Wenjuanxing / 问卷星 MCP Server

Empower your AI agent to orchestrate your data collection and research with Wenjuanxing (WJX), the premier online survey platform in China. By connecting Wenjuanxing to your agent, you transform complex questionnaire management, response auditing, and data analysis into a natural conversation. Your agent can instantly list your surveys, retrieve detailed structure and metadata, monitor real-time response counts, and even generate high-level analysis reports without you ever needing to navigate the comprehensive web interface. Whether you are conducting market research or auditing employee engagement, your agent acts as a real-time research assistant, keeping your data accurate and your insights moving.

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

What you can do

Survey Orchestration — List all questionnaires and retrieve detailed structure and metadata for each.
Response Monitoring — List and retrieve actual response data to monitor participation and engagement.
Analytical Reporting — Retrieve high-level summary reports and quantitative statistics for survey results.
Content Control — Create new survey structures and update the status of existing questionnaires.
Organization Insights — Browse survey folders and retrieve metadata about your Wenjuanxing account.

The Wenjuanxing / 问卷星 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 Wenjuanxing / 问卷星 to CrewAI via MCP

Follow these steps to integrate the Wenjuanxing / 问卷星 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 Wenjuanxing / 问卷星

Why Use CrewAI with the Wenjuanxing / 问卷星 MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Wenjuanxing / 问卷星 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 the 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

Wenjuanxing / 问卷星 + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Wenjuanxing / 问卷星 MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Wenjuanxing / 问卷星 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 Wenjuanxing / 问卷星, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Wenjuanxing / 问卷星 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 Wenjuanxing / 问卷星 against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Wenjuanxing / 问卷星 MCP Tools for CrewAI (10)

These 10 tools become available when you connect Wenjuanxing / 问卷星 to CrewAI via MCP:

create_survey

Create a new questionnaire

get_account_info

Get user account metadata

get_report

Get survey summary report

get_stats

Get survey statistics

get_survey

Get questionnaire details

list_groups

List survey groups

list_responses

List survey responses

list_surveys

List questionnaires

query_surveys

Search questionnaires by keyword

update_survey_status

g., publish, pause) of a specific survey. Update survey status

Example Prompts for Wenjuanxing / 问卷星 in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Wenjuanxing / 问卷星 immediately.

"List all active surveys in my Wenjuanxing account."

"Show me the responses for survey activity '8821'."

"What are the statistics for questionnaire '9920'?"

Troubleshooting Wenjuanxing / 问卷星 MCP Server with CrewAI

Common issues when connecting Wenjuanxing / 问卷星 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

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

Wenjuanxing / 问卷星 + CrewAI FAQ

Common questions about integrating Wenjuanxing / 问卷星 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.