How to Use the vCard Contacts Parser MCP in Google ADK

Q: Can I process contact lists using vCard Contacts Parser with Google ADK?

Yes, it converts massive iPhone and Android .vcf exports into clean JSON. This allows your agent to build a hyper-intelligent local address book that acts on existing cloud data.

Q: What types of data does vCard Contacts Parser handle for Google ADK?

It handles contact records from .vcf files, as well as structured text like highlights and notes extracted via parsekindleclippings. The output is always clean JSON.

Actionable intelligence for Google ADK: Structured data processing with the MCP Server.

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Connect vCard Contacts Parser MCP to Google ADK

Create your Vinkius account to connect vCard Contacts Parser to Google ADK 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 vCard Contacts Parser with Google ADK

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Parsing Kindle Clippings via MCP Server

The `parse_kindle_clippings` tool takes raw text from a Kindle's "My Clippings.txt" file and structures it into JSON. It extracts all highlights, notes, and bookmarks while correctly grouping them by the book they came from. This capability lets your Google ADK agent ingest academic or personal reading material directly into BigQuery for analysis.

VCard Contacts Parser with Google ADK

You can use the MCP Server to process bulk contact lists. It takes messy iPhone or Android `.vcf` files and structures them as clean JSON records, making your Gemini-powered agent a powerful local address book. This is ideal when integrating enterprise data housed in BigQuery with user contacts.

High-Volume Data Structuring for Google ADK

The MCP Server's core function is turning unstructured text into predictable JSON. Using `parse_kindle_clippings`, your agent reliably extracts data points—like notes and bookmarks—and organizes them, minimizing manual pre-processing steps. This fits perfectly with the large context window of Gemini models.

Setup guide

Set up vCard Contacts Parser MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with vCard Contacts Parser tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="vCard Contacts Parser_agent",
    model="gemini-2.0-flash",
    instruction="You have access to vCard Contacts Parser tools via MCP.",
    tools=mcp_tools,
)

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Common questions about vCard Contacts Parser MCP in Google ADK

You use the MCP Server to run the parsing toolset. Your agent then passes the resulting structured JSON data directly into BigQuery for long-context reasoning.

Yes, it converts massive iPhone and Android `.vcf` exports into clean JSON. This allows your agent to build a hyper-intelligent local address book that acts on existing cloud data.

It handles contact records from `.vcf` files, as well as structured text like highlights and notes extracted via `parse_kindle_clippings`. The output is always clean JSON.

The server handles contact information (VCF files). Since you are building enterprise agents on Google Cloud, keeping this sensitive data structured and contained within your BigQuery workflow is critical.

Yep. Beyond contacts, it reliably parses raw text exports—like Kindle clippings—grouping the extracted highlights and notes into a clean JSON format your agent can use.

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