How to Use the Google Contacts MCP in LlamaIndex

Q: Does LlamaIndex support real-time Google Contacts search?

Yes, the LlamaIndex agent can call searchcontacts directly to query live Google Contacts data. This bypasses the LlamaIndex vector index when you need real-time, exact-match information.

Q: How does the LlamaIndex agent handle Google Contacts groups?

The LlamaIndex agent uses listcontactgroups to retrieve your Google Contacts labels. It can then categorize Google Contacts dynamically based on the documents in your LlamaIndex index.

Index your Google Contacts into LlamaIndex vector stores to ground your agent in real address book data.

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Connect Google Contacts MCP to LlamaIndex

Create your Vinkius account to connect Google Contacts 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 Google Contacts with LlamaIndex

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Index Google Contacts for Semantic LlamaIndex Search

LlamaIndex ingest pipelines use `list_contacts` to turn your Google Contacts address book into searchable knowledge. Your LlamaIndex agent runs `list_contacts` to pull raw profiles, then indexes those records directly into a vector store. This lets you query your Google Contacts network using LlamaIndex semantic search instead of exact name matches. The LlamaIndex agent queries this local vector index before making external Google Contacts calls. When it needs to update someone, the LlamaIndex agent searches the index first, gets the correct ID, and then runs `get_contact` to verify the live Google Contacts record.

Ground Agent Responses in Live Google Contacts Data

Stop letting your LlamaIndex agent hallucinate email addresses by feeding live data from `search_contacts` directly into your Google Contacts RAG context. This MCP Server feeds live data from `search_contacts` directly into your LlamaIndex RAG pipeline context. Your LlamaIndex agent answers questions based on actual, live Google Contacts records. You define the Google Contacts data access pattern using the LlamaIndex tool spec. The LlamaIndex agent uses `get_contact_group` to pull specific Google Contacts lists, ensuring it only references relevant segments when generating replies.

Build Context-Aware Address Book Workflows

This integration lets you run `create_contact` based on context retrieved from your LlamaIndex vector store to update Google Contacts. Your LlamaIndex agent can read a PDF resume, search your vector store for similar profiles, and then run `create_contact` to add the candidate to Google Contacts. The LlamaIndex agent manages Google Contacts group categorization on the fly. It checks existing Google Contacts labels with `list_contact_groups` and assigns the new contact to the correct LlamaIndex-mapped category.

Setup guide

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

You use the LlamaIndex MCP tool spec to fetch Google Contacts data via `list_contacts`. The resulting Google Contacts documents are then loaded into your LlamaIndex vector index for semantic search.

Yes, the LlamaIndex agent can call `search_contacts` directly to query live Google Contacts data. This bypasses the LlamaIndex vector index when you need real-time, exact-match information.

Yes, you can pass an allowed tools filter to the LlamaIndex MCP adapter. This lets you restrict the LlamaIndex agent to read-only Google Contacts tools like `get_contact` and block write operations.

The LlamaIndex agent uses `list_contact_groups` to retrieve your Google Contacts labels. It can then categorize Google Contacts dynamically based on the documents in your LlamaIndex index.

No, your Google Contacts names and phone numbers are processed locally or sent only to your configured LlamaIndex LLM provider. The Vinkius MCP Server runs in a secure sandbox to protect your Google Contacts address book.

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