How to Use the Wenjuanxing / 问卷星 MCP in LlamaIndex

Q: Can I use LlamaIndex to track multiple Wenjuanxing / 问卷星 groups?

Yep. You can run listgroups repeatedly and index all the group names, descriptions, and IDs into your knowledge base. This makes finding specific groups much easier.

Q: Does LlamaIndex handle complex Wenjuanxing / 问卷星 data types?

It does. Whether it's raw text from listresponses or structured metadata from getaccountinfo, the output becomes part of a unified, queryable index.

Q: If I use LlamaIndex with an MCP Server, is the data safe?

The system supports allowedtools filtering and includeresources=True. This means you control exactly what parts of the Wenjuanxing / 问卷星 API are exposed to the index.

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Connect Wenjuanxing / 问卷星 MCP to LlamaIndex

Create your Vinkius account to connect Wenjuanxing / 问卷星 to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Wenjuanxing / 问卷星 with LlamaIndex

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Indexing MCP Server output in LlamaIndex

LlamaIndex doesn't just call tools; it indexes the results into a searchable knowledge base. For instance, if you run `list_surveys`, the resulting list of questionnaire titles and IDs becomes part of your indexed memory. You can then query past configurations semantically.

Querying Wenjuanxing / 问卷星 history with LlamaIndex

Want to know why a survey was paused last month? Use `update_survey_status` and record the context. Later, you query that past session through your RAG application, getting answers grounded in actual API data, not guesswork.

Advanced reporting using LlamaIndex

You combine live survey data with historical documents. For example, you can index the output of `get_stats` and then ask a natural language question like, 'What were the average scores for Q3?'—and get an answer based on that structured data.

Setup guide

Set up Wenjuanxing / 问卷星 MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Wenjuanxing / 问卷星 MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Wenjuanxing / 问卷星 tools.",
)
response = await agent.run("List recent Wenjuanxing / 问卷星 data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Wenjuanxing / 问卷星. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Wenjuanxing / 问卷星 MCP in LlamaIndex

It makes your API interactions searchable. Instead of just getting a single report, you build an index from all reports and configurations, letting you ask complex questions about the data history.

Yep. You can run `list_groups` repeatedly and index all the group names, descriptions, and IDs into your knowledge base. This makes finding specific groups much easier.

It does. Whether it's raw text from `list_responses` or structured metadata from `get_account_info`, the output becomes part of a unified, queryable index.

The system supports allowed_tools filtering and include_resources=True. This means you control exactly what parts of the Wenjuanxing / 问卷星 API are exposed to the index.

It indexes survey response metadata. This includes details about questionnaire status, group membership, and statistical summaries pulled from the API.

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