Modash MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Modash as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 Modash. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Modash?"
)
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 Modash MCP Server
Connect Modash to your AI agent to discover the perfect creators for your brand. Access a database of 350M+ influencers and get deep audience analytics through natural conversation.
LlamaIndex agents combine Modash tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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
- Influencer Search — Find creators based on followers, engagement rate, and location across major platforms.
- Audience Analytics — Get detailed reports on audience demographics, location, and authenticity.
- Platform Coverage — Seamlessly switch between Instagram, TikTok, and YouTube research.
- Dictionary Access — Easily find IDs for locations, interests, and brands to refine your searches.
- Real-time Data — Fetch the latest metrics and posts directly from influencer profiles.
The Modash MCP Server exposes 11 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 Modash to LlamaIndex via MCP
Follow these steps to integrate the Modash 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 11 tools from Modash
Why Use LlamaIndex with the Modash MCP Server
LlamaIndex provides unique advantages when paired with Modash through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Modash tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Modash tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Modash, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Modash tools were called, what data was returned, and how it influenced the final answer
Modash + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Modash MCP Server delivers measurable value.
Hybrid search: combine Modash real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Modash 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 Modash for fresh data
Analytical workflows: chain Modash queries with LlamaIndex's data connectors to build multi-source analytical reports
Modash MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Modash to LlamaIndex via MCP:
get_instagram_report
Get deep analytics for an Instagram profile
get_raw_profile
Get real-time, unfiltered profile data
get_tiktok_report
Get analytics for a TikTok profile
get_youtube_report
Get analytics for a YouTube channel
list_brands
Search for brand IDs
list_interests
Search for interest IDs
list_languages
Search for language IDs
list_locations
Search for location IDs
search_instagram
Search for Instagram influencers
search_tiktok
Search for TikTok influencers
search_youtube
Search for YouTube channels
Example Prompts for Modash in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Modash immediately.
"Search for Instagram influencers with 50k-100k followers in London."
"Get an audience report for the TikTok user @traveler_vlog."
"List all interest categories available for YouTube search."
Troubleshooting Modash MCP Server with LlamaIndex
Common issues when connecting Modash to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpModash + LlamaIndex FAQ
Common questions about integrating Modash 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 Modash 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 Modash to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.