How do I get my Medallia API credentials?

You need to contact your Medallia administrator to enable the REST API and create an OAuth 2.0 application to receive your Client ID and Secret.

What survey data can I access?

You can access survey configurations, individual responses, scores (like NPS), feedback comments, and metadata associated with each response.

Is my customer data secure?

Absolutely. Your credentials are encrypted at rest and injected securely at runtime.

Medallia MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Medallia
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 Medallia 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 Medallia. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Medallia?"
    )
    print(response)

asyncio.run(main())

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* 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 Medallia MCP Server

Connect your Medallia experience management instance to any AI agent and take full control of your customer feedback and CX programs through natural conversation.

LlamaIndex agents combine Medallia tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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 Management — List all customer surveys and fetch detailed configuration metadata
Feedback Monitoring — Retrieve and search survey responses to understand customer sentiment in real-time
Program Oversight — List and inspect experience management programs and their statuses
Alert Management — Monitor and retrieve details for alerts triggered by specific customer feedback
User Inventory — List authorized users and manage access within your Medallia instance

The Medallia 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 Medallia to LlamaIndex via MCP

Follow these steps to integrate the Medallia 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 Medallia

Why Use LlamaIndex with the Medallia MCP Server

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

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

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

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

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

Medallia + LlamaIndex Use Cases

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

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

Data enrichment: query Medallia 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 Medallia for fresh data

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

Medallia MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Medallia to LlamaIndex via MCP:

get_alert

Get details for a specific alert

get_program_details

Get details for a specific program

get_response

Get details for a specific response

get_survey

Get details for a specific survey

list_alerts

List feedback alerts

list_programs

List experience management programs

list_responses

List survey responses

list_surveys

List all customer surveys

list_users

List Medallia users

search_responses

Search survey responses by term

Example Prompts for Medallia in LlamaIndex

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

"List all active surveys in Medallia."

"Search responses for the term 'disappointed'."

"Show recent alerts from high-priority programs."

Troubleshooting Medallia MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Medallia + LlamaIndex FAQ

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