Mode Analytics MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mode Analytics as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
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 Mode Analytics. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Mode Analytics?"
)
print(response)
asyncio.run(main())
* 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 Mode Analytics MCP Server
Connect your Mode Analytics workspace to any AI agent and take full control of your data science and business intelligence workflows through natural conversation.
LlamaIndex agents combine Mode Analytics 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
- Workspace Oversight — List all spaces and members to maintain visibility over your analytical environment.
- Report Discovery — List and retrieve detailed metadata for reports across different spaces.
- Live Execution — Trigger new report runs directly through the agent, including support for custom parameters.
- Query Auditing — List the underlying SQL queries for any report to understand data lineage and logic.
- Definition Tracking — List calculated field definitions to ensure consistency in your metrics.
The Mode Analytics 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 Mode Analytics to LlamaIndex via MCP
Follow these steps to integrate the Mode Analytics 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 Mode Analytics
Why Use LlamaIndex with the Mode Analytics MCP Server
LlamaIndex provides unique advantages when paired with Mode Analytics through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Mode Analytics tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Mode Analytics tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Mode Analytics, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Mode Analytics tools were called, what data was returned, and how it influenced the final answer
Mode Analytics + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Mode Analytics MCP Server delivers measurable value.
Hybrid search: combine Mode Analytics real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Mode Analytics 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 Mode Analytics for fresh data
Analytical workflows: chain Mode Analytics queries with LlamaIndex's data connectors to build multi-source analytical reports
Mode Analytics MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Mode Analytics to LlamaIndex via MCP:
get_mode_account
Get authenticated account details
get_mode_report
Get details for a specific report
get_mode_report_run
Get details for a report run
list_mode_definitions
List calculated field definitions
list_mode_members
List workspace members
list_mode_queries
List SQL queries in a report
list_mode_report_runs
List runs for a report
list_mode_reports
List reports in a space
list_mode_spaces
List Mode Analytics spaces
run_mode_report
Trigger a new run for a report
Example Prompts for Mode Analytics in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Mode Analytics immediately.
"List all reports in the 'Marketing Analytics' space."
"Run the report with token 'rep_12345' and check its latest status."
"Show me the SQL query used in the 'Churn Analysis' report."
Troubleshooting Mode Analytics MCP Server with LlamaIndex
Common issues when connecting Mode Analytics to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMode Analytics + LlamaIndex FAQ
Common questions about integrating Mode Analytics MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Mode Analytics with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Mode Analytics to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.