How do I find my NavAPI Key?

Log in to your [**NavAPI dashboard**](https://navapi.com/), and you will find your API Key under the 'API Settings' or 'My Keys' section. Copy and paste it below.

Does it calculate real-world nautical distances?

Yes. The `get_port_distance` tool calculates the distance in nautical miles (NM) between two ports using established maritime routes.

Can the agent show vessel counts at ports?

Yes. The `get_port_vessel_traffic` tool provides real-time statistics on the number of vessels currently identified at a specific port.

NavAPI MCP Server for CrewAI 6 tools — connect in under 2 minutes

Name: NavAPI
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 6 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="NavAPI Specialist",
    goal="Help users interact with NavAPI effectively",
    backstory=(
        "You are an expert at leveraging NavAPI 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 NavAPI "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

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

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* 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 NavAPI MCP Server

Empower your AI agent to orchestrate your entire maritime research and nautical auditing workflow with NavAPI, the comprehensive source for global shipping and navigation data. By connecting NavAPI to your agent, you transform complex logistics searches into a natural conversation. Your agent can instantly search for maritime ports, audit nautical distances, and retrieve vessel traffic statistics without you ever touching a technical portal. Whether you are planning shipping routes or conducting regional maritime audits, your agent acts as a real-time nautical consultant, ensuring your data is always precise and localized.

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

What you can do

Port Auditing — Retrieve high-resolution details for thousands of global maritime ports, including country and coordinate metadata.
Route Oversight — Audit nautical distances between any two ports to maintain a clear view of shipping logistics and scale.
Traffic Intelligence — Query real-time vessel traffic for specific ports to understand the current industry distribution instantly.
Chart Discovery — List available nautical charts for specific geographic areas to assist in regional navigation planning.
Logistics Monitoring — Check API status to ensure your maritime research workflow is always operational.

The NavAPI MCP Server exposes 6 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect NavAPI to CrewAI via MCP

Follow these steps to integrate the NavAPI MCP Server with CrewAI.

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 6 tools from NavAPI

Why Use CrewAI with the NavAPI MCP Server

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

NavAPI + CrewAI Use Cases

Practical scenarios where CrewAI combined with the NavAPI MCP Server delivers measurable value.

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

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

NavAPI MCP Tools for CrewAI (6)

These 6 tools become available when you connect NavAPI to CrewAI via MCP:

check_api_status

Check if the NavAPI service is operational

get_nautical_ports

List global maritime ports with optional country filter

get_port_distance

Calculate the nautical distance between two ports

get_port_vessel_traffic

Get current vessel traffic statistics for a specific port

list_nautical_charts

List nautical charts available for a specific geographic area

search_maritime_routes

Search for maritime shipping routes

Example Prompts for NavAPI in CrewAI

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

"Search for ports in 'Singapore' using NavAPI."

"Calculate the nautical distance between 'SGSIN' (Singapore) and 'NLRTM' (Rotterdam)."

"What is the current traffic at the Port of Shanghai (CNSHA)?"

Troubleshooting NavAPI MCP Server with CrewAI

Common issues when connecting NavAPI to CrewAI through the 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.

NavAPI + CrewAI FAQ

Common questions about integrating NavAPI 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.