How do I obtain my Fairing API Key?

You can find your API Key in the Fairing admin portal under **Settings > Account**. Note that API access may depend on your current subscription plan.

Can I see responses for a specific customer?

Yes! Use the `get_customer_responses` tool with the specific Customer ID to retrieve all survey feedback associated with that individual.

What kind of insights can I extract?

The `get_insights` tool provides aggregated data on question performance, response rates, and attribution trends across your survey streams.

Fairing MCP Server for LlamaIndex 12 tools — connect in under 2 minutes

Name: Fairing
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 12 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Fairing as an MCP tool provider through 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 Fairing. "
            "You have 12 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Fairing?"
    )
    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 Fairing MCP Server

Connect your Fairing (formerly EnquireLabs) account to any AI agent and take full control of your post-purchase surveys and zero-party data through natural conversation.

LlamaIndex agents combine Fairing tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through 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 & Question Management — List all active questions and fetch detailed configurations for your post-purchase surveys
Response Tracking — List and inspect individual survey responses to understand customer sentiment and attribution
Zero-Party Data Analysis — Query customer-specific responses to pair survey data with your marketing profiles
Aggregated Insights — Extract high-level insights and performance metrics across all your survey streams
Integration Audit — Monitor active integrations with platforms like Klaviyo, GA4, and Meta directly from the cloud
Account Context — Retrieve your Fairing account details and API token identity flawlessly

The Fairing MCP Server exposes 12 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 Fairing to LlamaIndex via MCP

Follow these steps to integrate the Fairing 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 12 tools from Fairing

Why Use LlamaIndex with the Fairing MCP Server

LlamaIndex provides unique advantages when paired with Fairing through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Fairing tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Fairing tool calls with transformations, filters, and re-rankers in a typed pipeline

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

Observability integrations show exactly what Fairing tools were called, what data was returned, and how it influenced the final answer

Fairing + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Fairing MCP Server delivers measurable value.

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

Data enrichment: query Fairing 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 Fairing for fresh data

Analytical workflows: chain Fairing queries with LlamaIndex's data connectors to build multi-source analytical reports

Fairing MCP Tools for LlamaIndex (12)

These 12 tools become available when you connect Fairing to LlamaIndex via MCP:

get_account_info

Get Fairing account information

get_customer_responses

Get all survey responses for a specific customer

get_insights

Get aggregated survey insights

get_me

Get current API token identity

get_question

Get details for a specific survey question

get_response

Get details for a specific survey response

get_survey_details

Get details for a specific survey

list_customers

List customers who have interacted with surveys

list_integrations

List active Fairing integrations

list_questions

List all Fairing survey questions

list_responses

List all survey responses

list_surveys

List all Fairing surveys

Example Prompts for Fairing in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Fairing immediately.

"List all active survey questions on Fairing."

"Show me the latest 5 survey responses."

"Check my active integrations on Fairing."

Troubleshooting Fairing MCP Server with LlamaIndex

Common issues when connecting Fairing to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Fairing + LlamaIndex FAQ

Common questions about integrating Fairing 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 Fairing tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.