How to Use the Untappd MCP in LlamaIndex

Q: Can Untappd and LlamaIndex handle multiple data sources?

Yes. You can combine live API calls (e.g., getuserfriends) with static documents in a single unified index, making your application much more powerful than simple tool calling.

Q: If I want to track beer history using Untappd and LlamaIndex?

You can pull all distinct beers via getuserdistinctbeers, index the list, and then build a custom query that asks about rarity or geographic clustering based on the indexed data.

Build searchable knowledge bases from Untappd data using your AI client and the LlamaIndex MCP Server.

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Connect Untappd MCP to LlamaIndex

Create your Vinkius account to connect Untappd 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 Untappd with LlamaIndex

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Indexing Beer Metadata with LlamaIndex

LlamaIndex turns ephemeral API results into permanent, searchable knowledge. You can use `get_beer_info` to pull beer details; the output gets indexed immediately. Later, you query that data—like finding all beers over 7% ABV—without needing to call the original tool again.

Querying Social Activity via MCP Server

Don't just read a feed; search it. You can pull friend activity using `get_friend_activity` and index that data. Your RAG application then lets you ask, 'What did John drink last Tuesday?' and get an answer grounded in the actual API output.

Managing Venues for LlamaIndex

The server supports venue-based lookups. You can use `foursquare_lookup` to translate IDs, then get activity using `get_venue_activity`. Indexing this data lets you build a knowledge base of popular spots and what people are drinking there.

Setup guide

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

LlamaIndex takes the structured output from an MCP tool, like `get_user_info`, and converts it into vector embeddings. This allows your AI client to search the data semantically later on.

Yes. You can combine live API calls (e.g., `get_user_friends`) with static documents in a single unified index, making your application much more powerful than simple tool calling.

You can pull all distinct beers via `get_user_distinct_beers`, index the list, and then build a custom query that asks about rarity or geographic clustering based on the indexed data.

No. The Vinkius MCP Server handles all authentication internally, so you just need to ensure your AI client has the correct endpoint token to access the tools like `search_beer`.

This server touches various personal records. These include `user profile information`, friend lists (`get_user_friends`), and detailed check-in history associated with the user's account.

Use it with your favorite AI tools

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