How to Use the Modash MCP in LlamaIndex

Q: How do I limit which Modash MCP Server tools LlamaIndex can access?

You can use the allowedtools filter when setting up your McpToolSpec. This lets you restrict the LlamaIndex agent to discovery tools like searchtiktok while hiding administrative endpoints.

Index live social metrics from Modash directly into your LlamaIndex vector store using this MCP Server.

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Connect Modash MCP to LlamaIndex

Create your Vinkius account to connect Modash 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 Modash with LlamaIndex

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LlamaIndex grounded RAG with fresh social metrics

The `get_instagram_report` and `get_tiktok_report` tools retrieve fresh social metrics that LlamaIndex indexes for grounded RAG. Your LlamaIndex agent queries this index to answer questions about creator performance. Because the data is grounded in real-time API responses, your system avoids the hallucinated metrics common in standard language models.

Semantic search over creator profiles

The `get_raw_profile` and `get_youtube_report` tools feed real-time creator data directly into your LlamaIndex vector store. You can query this indexed Modash data using natural language to find which creators have the highest engagement in specific regions. LlamaIndex searches the indexed tool outputs to find the exact matches, bypassing manual database queries.

Querying structured platform taxonomies

The `list_interests` and `list_locations` tools supply valid platform taxonomy codes to your LlamaIndex query engine. LlamaIndex indexes these taxonomies so your agent can map loose user queries to exact platform categories. This ensures your Modash search parameters are always valid before hitting the live APIs.

Setup guide

Set up Modash 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 Modash 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 Modash tools.",
)
response = await agent.run("List recent Modash data")

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Common questions about Modash MCP in LlamaIndex

You use the llama-index-tools-mcp package to initialize the client. The tool outputs from `get_youtube_report` or other endpoints can then be loaded as documents and indexed into your LlamaIndex vector store.

Yes. You can build a query engine that merges your internal campaign PDFs with live metrics retrieved via `get_instagram_report` to generate creator briefs.

You can use the allowed_tools filter when setting up your McpToolSpec. This lets you restrict the LlamaIndex agent to discovery tools like `search_tiktok` while hiding administrative endpoints.

LlamaIndex handles the indexing of the retrieved data, but you control the cache lifecycle. You can re-run tools like `get_raw_profile` to update your LlamaIndex vector index whenever metrics change.

Your API key is handled securely by Vinkius and is never stored in your LlamaIndex vector database. Only the public influencer metrics and audience demographics returned by the tools are indexed.

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