HypeAuditor 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 HypeAuditor as an MCP tool provider through the 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 HypeAuditor. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in HypeAuditor?"
)
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 HypeAuditor MCP Server
Empower your AI agents with HypeAuditor's industry-leading influencer analytics. This MCP server allows you to search for influencers across Instagram, YouTube, and TikTok, retrieve detailed audit reports, and manage your account insights directly through the HypeAuditor API. Ideal for data-driven influencer marketing and brand protection.
LlamaIndex agents combine HypeAuditor tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
The HypeAuditor 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 HypeAuditor to LlamaIndex via MCP
Follow these steps to integrate the HypeAuditor 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 HypeAuditor
Why Use LlamaIndex with the HypeAuditor MCP Server
LlamaIndex provides unique advantages when paired with HypeAuditor through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine HypeAuditor tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain HypeAuditor tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query HypeAuditor, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what HypeAuditor tools were called, what data was returned, and how it influenced the final answer
HypeAuditor + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the HypeAuditor MCP Server delivers measurable value.
Hybrid search: combine HypeAuditor real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query HypeAuditor 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 HypeAuditor for fresh data
Analytical workflows: chain HypeAuditor queries with LlamaIndex's data connectors to build multi-source analytical reports
HypeAuditor MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect HypeAuditor to LlamaIndex via MCP:
get_account_info
Gets your HypeAuditor account details
get_influencer_report
Retrieves a detailed report for an influencer
get_rate_limit
Gets current API rate limit status
list_categories
Lists influencer categories
list_countries
Lists available countries
list_influencer_types
Lists available influencer types
list_languages
Lists available languages
list_platforms
Lists supported social media platforms
list_reports
Lists reports generated in your account
search_influencers
Searches for influencers with filters
Example Prompts for HypeAuditor in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with HypeAuditor immediately.
"Search for fashion influencers in France on Instagram."
"Get an audit report for influencer ID 'xyz-123'."
"Check my current API rate limit and credits."
Troubleshooting HypeAuditor MCP Server with LlamaIndex
Common issues when connecting HypeAuditor to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHypeAuditor + LlamaIndex FAQ
Common questions about integrating HypeAuditor 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 HypeAuditor 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 HypeAuditor to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.