vCard Contacts Parser MCP Server for CrewAIGive CrewAI 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

Connect your CrewAI agents to vCard Contacts Parser through Vinkius, pass the Edge URL in the `mcps` parameter and every vCard Contacts Parser tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Ask AI about this MCP Server for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The vCard Contacts Parser MCP Server for CrewAI 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

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="vCard Contacts Parser Specialist",
    goal="Help users interact with vCard Contacts Parser effectively",
    backstory=(
        "You are an expert at leveraging vCard Contacts Parser tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in vCard Contacts Parser "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 1 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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.

When paired with CrewAI, vCard Contacts Parser becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call vCard Contacts Parser tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI

When CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 1 tools from vCard Contacts Parser

Why Use CrewAI with the vCard Contacts Parser MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with vCard Contacts Parser through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

vCard Contacts Parser + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries vCard Contacts Parser for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries vCard Contacts Parser, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain vCard Contacts Parser tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries vCard Contacts Parser against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for vCard Contacts Parser in CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

vCard Contacts Parser + CrewAI FAQ

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

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.