IP Address Parser MCP Server for CrewAIGive CrewAI instant access to 1 tools to Parse Ip Address

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

GDPR Free for Subscribers

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

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The IP Address Parser MCP Server for CrewAI is a standout in the Loved By Devs category — giving your AI agent 1 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="IP Address Parser Specialist",
    goal="Help users interact with IP Address Parser effectively",
    backstory=(
        "You are an expert at leveraging IP Address 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 IP Address 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)

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About IP Address Parser MCP Server

A security agent receives the IP 10.0.14.7 and needs to know: is this a private address? Can it reach the internet? What CIDR block does it belong to? Ask an AI and you'll get a confident but often wrong answer.

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

This MCP uses ipaddr.js (30M+ weekly downloads) — the exact same library that Express.js, Koa, and Fastify use to parse IP addresses in production. Every classification follows RFC 5735 and RFC 4291.

The Superpowers

Range Classification: Instantly know if an IP is unicast, private, loopback, multicast, linkLocal, or unspecified — no RFC memorization needed.
CIDR Parsing: Pass 10.0.0.0/8 and get the network address, prefix length, and address kind.
Dual Stack: Full IPv4 and IPv6 support with automatic format detection.
IPv4↔IPv6 Conversion: Convert 192.168.1.1 to its IPv4-mapped IPv6 representation ::ffff:192.168.1.1 and back.

The IP Address 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 IP Address Parser tools available for CrewAI

When CrewAI connects to IP Address Parser through Vinkius, your AI agent gets direct access to every tool listed below — spanning ipv4, ipv6, cidr, 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 ip address on IP Address Parser

The engine uses ipaddr.js (30M+ downloads) which is the standard IP parsing library used by Express.js and Koa. Validates and parses IPv4/IPv6 addresses. Supports CIDR notation, range detection, and IPv4↔IPv6 conversion

Connect IP Address Parser to CrewAI via MCP

Follow these steps to wire IP Address 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 IP Address Parser

Why Use CrewAI with the IP Address Parser MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with IP Address 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

IP Address Parser + CrewAI Use Cases

Practical scenarios where CrewAI combined with the IP Address Parser MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries IP Address 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 IP Address Parser, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain IP Address 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 IP Address Parser against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for IP Address Parser in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with IP Address Parser immediately.

"Our firewall received a connection from 10.0.14.7. Is this an internal or external IP?"

"Parse the VPC subnet 172.31.0.0/16 for our AWS infrastructure documentation."

"Convert our on-prem server 192.168.1.100 to IPv6 format for the dual-stack migration."

Troubleshooting IP Address Parser MCP Server with CrewAI

Common issues when connecting IP Address 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.

IP Address Parser + CrewAI FAQ

Common questions about integrating IP Address 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.

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