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 LlamaIndex 10 tools — connect in under 2 minutes

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

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Wenjuanxing / 问卷星 as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Wenjuanxing / 问卷星. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Wenjuanxing / 问卷星?"
    )
    print(response)

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 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.

LlamaIndex agents combine Wenjuanxing / 问卷星 tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the Wenjuanxing / 问卷星 MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

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 Wenjuanxing / 问卷星

Why Use LlamaIndex with the Wenjuanxing / 问卷星 MCP Server

LlamaIndex provides unique advantages when paired with Wenjuanxing / 问卷星 through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Wenjuanxing / 问卷星 tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Wenjuanxing / 问卷星 tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Wenjuanxing / 问卷星, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Wenjuanxing / 问卷星 tools were called, what data was returned, and how it influenced the final answer

Wenjuanxing / 问卷星 + LlamaIndex Use Cases

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

Hybrid search: combine Wenjuanxing / 问卷星 real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Wenjuanxing / 问卷星 to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Wenjuanxing / 问卷星 for fresh data

Analytical workflows: chain Wenjuanxing / 问卷星 queries with LlamaIndex's data connectors to build multi-source analytical reports

Wenjuanxing / 问卷星 MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Wenjuanxing / 问卷星 to LlamaIndex 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 LlamaIndex

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

Common issues when connecting Wenjuanxing / 问卷星 to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Wenjuanxing / 问卷星 + LlamaIndex FAQ

Common questions about integrating Wenjuanxing / 问卷星 MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Wenjuanxing / 问卷星 tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.