How to Use the Culture Amp MCP in LlamaIndex

Q: Can I filter which Culture Amp tools LlamaIndex can access?

Yes, you can use the allowedtools filter when initializing the MCP Server tool spec in LlamaIndex. This lets you restrict your RAG agent to read-only tools like listemployees while blocking mutation tools.

Q: How does LlamaIndex prevent hallucinations in Culture Amp reports?

LlamaIndex grounds its answers by querying listanalyticsdatasets directly before responding. The agent uses the actual dataset schemas returned by the Culture Amp MCP Server rather than guessing the structure of your reports.

Q: Can I use this MCP Server to build a hybrid HR search with LlamaIndex?

Yes, you can combine live API data from tools like searchemployeesbyname with static HR PDF policies indexed in LlamaIndex. This gives your agent a complete view of both company rules and actual employee files.

Index Culture Amp survey results and employee directories into LlamaIndex vector stores for grounded RAG queries.

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Connect Culture Amp MCP to LlamaIndex

Create your Vinkius account to connect Culture Amp 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 Culture Amp with LlamaIndex

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Index Culture Amp directories for semantic search

The `list_employees` tool pulls active employee profiles directly into your LlamaIndex data ingestion pipeline. This tool acts as a live data source, feeding employee details into your vector store. LlamaIndex then parses these profiles to create a searchable index of your organization. When you query your agent about team structures, it pulls live data from the Culture Amp MCP Server instead of relying on stale offline documents.

Ground survey analysis in real-time metadata

The `get_survey_details` tool retrieves configuration and participant counts from active Culture Amp feedback cycles. This tool provides the raw context your LlamaIndex RAG application needs to query our MCP Server for specific survey progress. Your agent combines this tool with `list_demographic_fields` to index how different segments are mapped. The resulting index ensures that your agent's reports on survey participation are fully grounded in actual organizational boundaries.

Query organizational groups via LlamaIndex RAG

The `list_organizational_groups` tool maps your company's team hierarchies and classifications directly into LlamaIndex. This tool feeds the exact team structures into your knowledge graph to preserve reporting relationships. By indexing these groups alongside `get_employee_details`, your LlamaIndex agent can accurately answer complex organizational questions. You get a queryable knowledge base that understands exactly who reports where without manual mapping.

Setup guide

Set up Culture Amp 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 Culture Amp 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 Culture Amp tools.",
)
response = await agent.run("List recent Culture Amp data")

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Common questions about Culture Amp MCP in LlamaIndex

Use llama-index-tools-mcp to load the Culture Amp tools into your environment. You can then run tools like list_engagement_surveys and feed the resulting JSON directly into your LlamaIndex vector storage.

Yes, you can use the allowed_tools filter when initializing the MCP Server tool spec in LlamaIndex. This lets you restrict your RAG agent to read-only tools like list_employees while blocking mutation tools.

LlamaIndex grounds its answers by querying list_analytics_datasets directly before responding. The agent uses the actual dataset schemas returned by the Culture Amp MCP Server rather than guessing the structure of your reports.

Yes, you can combine live API data from tools like search_employees_by_name with static HR PDF policies indexed in LlamaIndex. This gives your agent a complete view of both company rules and actual employee files.

The server isolates all requests to your survey settings and analytics data within a zero-trust, ephemeral environment. Your API keys are managed securely by Vinkius, meaning your LlamaIndex client only needs a single endpoint token to read data.

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