How to Use the AskNicely MCP in LlamaIndex

Q: How do I ingest AskNicely data into LlamaIndex?

Use BasicMCPClient to connect to the endpoint. Call totoollistasync() and pass the resulting tools to your FunctionAgent to start pulling responses.

Q: Can LlamaIndex search through past AskNicely surveys?

Yes. Your agent uses listresponses to fetch the data, which you then embed into your index. Users can run semantic queries against the raw feedback.

Q: How do I check if my AskNicely credentials work in LlamaIndex?

The getaccountcheck tool verifies the connection instantly. Run it before kicking off a massive indexing job.

Index AskNicely customer feedback directly into your LlamaIndex vector stores via this MCP integration.

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Connect AskNicely MCP to LlamaIndex

Create your Vinkius account to connect AskNicely 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 AskNicely with LlamaIndex

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Build RAG on AskNicely Responses

Customer feedback usually dies in a dashboard. By connecting the AskNicely MCP Server to LlamaIndex, you turn raw NPS text into a queryable knowledge base. Your application calls `list_responses` and ingests the actual survey comments. Those responses become embedded documents in your vector store. When an executive asks why churn is up, your RAG pipeline searches the exact complaints from last week. Grounded answers replace guesswork.

Query Aggregate NPS Statistics

Sometimes you need the hard numbers alongside the text. The `get_statistics` tool gives your FunctionAgent the current baseline scores. It pulls the aggregate data before running semantic searches on the qualitative feedback. Combining these inputs gives your index deep context. The agent knows the overall score dropped by five points, and the vector search explains exactly which features caused the anger.

Trigger Surveys from LlamaIndex

RAG applications don't have to be read-only. You can configure your FunctionAgent to reach out to specific users based on retrieved documents. Calling `trigger_survey` adds a contact and sends an NPS prompt right away. Verifying the setup takes one step. The agent runs `get_account_check` to confirm API access, then uses `list_contacts` to ensure it targets the right audience. It closes the loop between reading past feedback and asking for new input.

Setup guide

Set up AskNicely 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 AskNicely 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 AskNicely tools.",
)
response = await agent.run("List recent AskNicely 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 AskNicely. 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 AskNicely MCP in LlamaIndex

Use BasicMCPClient to connect to the endpoint. Call to_tool_list_async() and pass the resulting tools to your FunctionAgent to start pulling responses.

Yes. Your agent uses list_responses to fetch the data, which you then embed into your index. Users can run semantic queries against the raw feedback.

You can restrict your agent to specific operations. Passing just get_statistics prevents the indexer from accidentally triggering new surveys.

The get_account_check tool verifies the connection instantly. Run it before kicking off a massive indexing job.

Security is built into the Vinkius architecture via ephemeral sandboxes. When your agent fetches user records via list_contacts, the PII passes through a zero-trust tunnel straight to your vector store. Nothing is saved on our end.

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