Compatible with every major AI agent and IDE
What is the 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.
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
10.0.0.0/8and get the network address, prefix length, and address kind. - Dual Stack: Full IPv4 and IPv6 support with automatic format detection.
- IPv4↔IPv6 Conversion: Convert
192.168.1.1to its IPv4-mapped IPv6 representation::ffff:192.168.1.1and back.
Built-in capabilities (1)
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
Why CrewAI?
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.
- —
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
mcpsparameter 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 in CrewAI
IP Address Parser and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect IP Address Parser to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for IP Address Parser in CrewAI
The IP Address Parser 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. All 1 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
IP Address Parser for CrewAI
Every tool call from CrewAI to the IP Address Parser MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How does it know if an IP is private or public?
It follows the IANA reserved ranges defined in RFC 5735 (IPv4) and RFC 4291 (IPv6). 10.x.x.x, 172.16-31.x.x, and 192.168.x.x are classified as 'private'. 127.x.x.x as 'loopback'. Everything else as 'unicast' (public).
Can I check if an IP belongs to a specific CIDR range?
Yes. Pass the CIDR notation like '10.0.0.0/8' and the engine returns the network address, prefix length, and address kind. Parse both the IP and the CIDR to compare.
Does it work with IPv6 addresses?
Yes. Full IPv6 support including compressed notation (::1), IPv4-mapped (::ffff:192.168.1.1), and all RFC 4291 scoped addresses.
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.
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.
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