How to Use the Gainsight CS MCP in LlamaIndex

Q: Can LlamaIndex query live Gainsight CS health scores?

Yes, your LlamaIndex query engine can call getcompanyhealth dynamically during the retrieval phase. This ensures that the generated LlamaIndex answers are grounded in real-time Gainsight CS customer health metrics rather than static, cached data.

Build RAG pipelines that index live Gainsight CS customer health data and timeline logs directly into LlamaIndex vector stores using this MCP Server.

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Connect Gainsight CS MCP to LlamaIndex

Create your Vinkius account to connect Gainsight CS 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 Gainsight CS with LlamaIndex

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Build LlamaIndex RAG pipelines with this MCP Server

The Gainsight CS MCP Server lets you turn customer interactions from `list_timeline_events` into searchable LlamaIndex vector embeddings. By calling `list_timeline_events`, your LlamaIndex pipeline can index past notes and meetings directly into your local vector database. That's how you ground your queries. This integration allows your LlamaIndex agent to query historical Gainsight CS interactions semantically rather than relying on exact keyword matches. When a customer raises an issue, the LlamaIndex agent pulls contextual Gainsight CS history instantly to ground its responses in actual account history.

Ground your queries in live Gainsight CS health metrics

The `get_company_health` tool provides live customer metrics to prevent your LlamaIndex agent from referencing outdated Gainsight CS account details. LlamaIndex combines this structured Gainsight CS metadata with unstructured documents to give your LLM a complete view of the account's current status. This prevents your LlamaIndex agent from hallucinating account health or referencing stale Gainsight CS subscription details. Querying `list_customer_companies` lets the LlamaIndex pipeline verify the Gainsight CS company's profile before generating any customer-facing summaries.

Synthesize cockpit tasks with historical customer profiles

The `list_cockpit_tasks` tool lets your LlamaIndex pipeline retrieve outstanding actions to match them against Gainsight CS customer profiles. Your LlamaIndex pipeline retrieves Gainsight CS task details using `get_task_metadata` and indexes them alongside the person's records. This combined LlamaIndex index helps account teams quickly understand the context behind open Gainsight CS calls to action. By calling `get_person_details`, the LlamaIndex agent links technical tasks to real people, providing a clearer picture of who needs attention.

Setup guide

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

Use the MCP tool spec to fetch live data from Gainsight CS endpoints like `list_timeline_events`. You can then convert these Gainsight CS tool outputs into document objects and insert them directly into your LlamaIndex index structure.

Yes, your LlamaIndex query engine can call `get_company_health` dynamically during the retrieval phase. This ensures that the generated LlamaIndex answers are grounded in real-time Gainsight CS customer health metrics rather than static, cached data.

The McpToolSpec class automatically translates the Gainsight CS server's tools into a list of function tools that your LlamaIndex agent can call. This maps parameters for Gainsight CS tools like `list_customer_companies` without manual schema editing in LlamaIndex.

You can pass an allowed tools list to your LlamaIndex agent configuration to restrict access. This restricts the LlamaIndex agent to specific operations, such as only letting it view Gainsight CS tasks via `list_cockpit_tasks` while blocking modification tools.

Your Gainsight CS customer profiles and timeline logs are never persisted on Vinkius servers. All data retrieved via `get_person_details` or `list_crm_people` is streamed over an encrypted connection directly to your local LlamaIndex instance, maintaining strict data isolation for your Gainsight CS records.

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