NavAPI MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add NavAPI as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to NavAPI. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in NavAPI?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine NavAPI tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the NavAPI MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 6 tools from NavAPI
Why Use LlamaIndex with the NavAPI MCP Server
LlamaIndex provides unique advantages when paired with NavAPI through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine NavAPI tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain NavAPI tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query NavAPI, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what NavAPI tools were called, what data was returned, and how it influenced the final answer
NavAPI + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the NavAPI MCP Server delivers measurable value.
Hybrid search: combine NavAPI real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query NavAPI to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying NavAPI for fresh data
Analytical workflows: chain NavAPI queries with LlamaIndex's data connectors to build multi-source analytical reports
NavAPI MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect NavAPI to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting NavAPI to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpNavAPI + LlamaIndex FAQ
Common questions about integrating NavAPI MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect NavAPI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect NavAPI to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.