vCard Contacts Parser MCP Server for LangChainGive LangChain instant access to 1 tools to Parse Kindle Clippings

Name: vCard Contacts Parser
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect vCard Contacts Parser through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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The vCard Contacts Parser MCP Server for LangChain is a standout in the Productivity category — giving your AI agent 1 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "vcard-contacts-parser": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using vCard Contacts Parser, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 vCard Contacts Parser MCP Server

When you export your phone's address book, you get a massive .vcf file containing hundreds of contacts formatted in the legacy BEGIN:VCARD structure, often bloated with base64-encoded profile pictures. If you ask an LLM to read this raw file, it will exhaust its context window and hallucinate phone numbers and emails.

LangChain's ecosystem of 500+ components combines seamlessly with vCard Contacts Parser through native MCP adapters. Connect 1 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

This MCP is a dedicated contact intelligence engine. It runs 100% local on your machine, instantly stripping away the binary noise and converting the raw vCard format into a beautiful, easily queryable JSON array. The AI sees exactly what it needs: First Name, Last Name, Organization, Phone, and Email.

The Superpowers

100% Air-Gapped Privacy: Your personal phonebook never leaves your local machine.
Zero Hallucination: Perfect extraction of country codes, emails, and company roles.
Massive File Support: Can instantly process a VCF file containing 5,000+ contacts.
Assistant Ready: Ask your AI: 'Find the phone number for the CTO of Vinkius in my contacts.'

The vCard Contacts Parser MCP Server exposes 1 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 1 vCard Contacts Parser tools available for LangChain

When LangChain connects to vCard Contacts Parser through Vinkius, your AI agent gets direct access to every tool listed below — spanning vcard, contact-parsing, data-extraction, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

parse

Parse kindle clippings on vCard Contacts Parser

Paste the raw text content from the "My Clippings.txt" file found on a Kindle device. Parse Amazon Kindle "My Clippings.txt" exports into structured JSON. Extracts highlights, notes, and bookmarks grouped by book

Connect vCard Contacts Parser to LangChain via MCP

Follow these steps to wire vCard Contacts Parser into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 1 tools from vCard Contacts Parser via MCP

Why Use LangChain with the vCard Contacts Parser MCP Server

LangChain provides unique advantages when paired with vCard Contacts Parser through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine vCard Contacts Parser MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across vCard Contacts Parser queries for multi-turn workflows

vCard Contacts Parser + LangChain Use Cases

Practical scenarios where LangChain combined with the vCard Contacts Parser MCP Server delivers measurable value.

RAG with live data: combine vCard Contacts Parser tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query vCard Contacts Parser, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain vCard Contacts Parser tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every vCard Contacts Parser tool call, measure latency, and optimize your agent's performance

Example Prompts for vCard Contacts Parser in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with vCard Contacts Parser immediately.

"Search my contacts.vcf and give me a list of everyone who works at 'Vinkius'."

"Extract all the email addresses from this vCard export and format them as a CSV."

"Look through my contacts and find the phone number for 'Plumber'."

Troubleshooting vCard Contacts Parser MCP Server with LangChain

Common issues when connecting vCard Contacts Parser to LangChain through Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

vCard Contacts Parser + LangChain FAQ

Common questions about integrating vCard Contacts Parser MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.