How to Use the CONSENSUS MCP in LlamaIndex

Q: Can I index CONSENSUS demo analytics using LlamaIndex?

Yes, you can fetch raw metrics using listdemolytics and load them into a LlamaIndex vector store. The LlamaIndex agent can then search this index to answer complex questions about user engagement. This keeps your RAG applications grounded in real-time CONSENSUS sales data.

Q: How does the LlamaIndex agent handle large lists of CONSENSUS demo invitations?

The LlamaIndex agent fetches the data in chunks using listinvitations and indexes them as document nodes. LlamaIndex handles the chunking and embedding, so your agent doesn't hit token limits when analyzing thousands of CONSENSUS invites.

Index live CONSENSUS demo analytics directly into your LlamaIndex vector store using this MCP Server.

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Connect CONSENSUS MCP to LlamaIndex

Create your Vinkius account to connect CONSENSUS 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 CONSENSUS with LlamaIndex

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Index CONSENSUS demo engagement data for LlamaIndex RAG

Turn raw CONSENSUS metrics into searchable knowledge. Your LlamaIndex agent calls `list_demolytics` and indexes the viewer behavior data, allowing you to ask natural language questions about which features are getting the most attention. Instead of reading raw JSON, your LlamaIndex query engine searches through the indexed demo records. You get immediate answers about prospect intent grounded in actual CONSENSUS usage data.

Semantic search over CONSENSUS demoboards via MCP Server

Feed your LlamaIndex vector database with live board data by running `list_demoboards` through this server. The agent converts the CONSENSUS board names, descriptions, and viewer lists into document nodes for semantic search. When a rep asks LlamaIndex which boards are active for a specific enterprise account, the agent retrieves the exact match from the index. It can also pull deep details on a specific CONSENSUS board using `get_demoboard` on the fly.

Query CONSENSUS invitation history and user lists

Let your LlamaIndex agent build a local index of your team structure and sent invites using `list_users` and `list_invitations`. This lets you query who sent what CONSENSUS demo and when, directly from your terminal. The agent matches CONSENSUS invitation statuses with internal user names to find bottlenecks in your sales cycle. You can query the LlamaIndex index to see which reps are sending the most high-performing demos without writing SQL.

Setup guide

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

You use the llama-index-tools-mcp package to initialize the MCP client. Then, convert the CONSENSUS tools to a standard tool list using the asynchronous helper. Pass that list to your LlamaIndex FunctionAgent to start querying demo data.

Yes, you can fetch raw metrics using `list_demolytics` and load them into a LlamaIndex vector store. The LlamaIndex agent can then search this index to answer complex questions about user engagement. This keeps your RAG applications grounded in real-time CONSENSUS sales data.

Yes, you can use the allowed tools filter during LlamaIndex initialization to restrict what the agent can access. For example, you can expose only `list_demos` while keeping CONSENSUS user management tools hidden. This gives you granular control over agent capabilities.

The LlamaIndex agent fetches the data in chunks using `list_invitations` and indexes them as document nodes. LlamaIndex handles the chunking and embedding, so your agent doesn't hit token limits when analyzing thousands of CONSENSUS invites.

Vinkius runs the MCP server in a zero-trust, ephemeral sandbox that isolates your CONSENSUS user lists and demo configurations from external networks. Your credentials are never cached or exposed to LlamaIndex vector databases. Every transaction is encrypted and discarded immediately after the tool call completes.

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