How to Use the Mode Analytics MCP in LlamaIndex

Q: How does LlamaIndex index Mode Analytics data?

The server feeds output from tools like runmodereport into your vector store. LlamaIndex then parses these results, making them part of your searchable knowledge.

Q: Can I filter which Mode Analytics reports LlamaIndex sees?

Absolutely. You can use the allowedtools filter during setup to restrict your agent to specific reports or workspaces.

Index live Mode Analytics data into your LlamaIndex knowledge base to ground your AI in real-time reporting.

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Connect Mode Analytics MCP to LlamaIndex

Create your Vinkius account to connect Mode Analytics 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 Mode Analytics with LlamaIndex

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Ground AI in live report data

Use `run_mode_report` to pull the latest results into your index. LlamaIndex then processes this data, making it searchable for future queries. This keeps your RAG application current. You aren't relying on stale documents; you are querying the live output of your internal analytics platform.

Query past report metadata

Call `list_mode_reports` to catalog available dashboards. Once indexed, your agent knows exactly which report contains the specific metrics you need. It saves time on discovery. Instead of hunting through URLs, your agent scans the list and builds a searchable map of your entire workspace.

Audit runs and query logic

Pull execution history with `list_mode_report_runs` and cross-reference it with `list_mode_queries`. Your index now contains the context of how your data was calculated. This adds depth to your answers. When asked about a specific number, your agent finds the exact query and run details that generated it.

Setup guide

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

The server feeds output from tools like `run_mode_report` into your vector store. LlamaIndex then parses these results, making them part of your searchable knowledge.

Absolutely. You can use the allowed_tools filter during setup to restrict your agent to specific reports or workspaces.

Only if you configure your index to store it. The server itself is just an interface, so you control how long the data persists in your local knowledge base.

The server uses your provided credentials to authenticate every call. Data is transferred directly to your agent's memory or index without intermediate storage.

You can trigger updates by calling the tools on a schedule. Your index will then refresh with the latest data retrieved by the server.

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