How to Use the NOAA Tides & Currents API MCP in AutoGen

Q: Can my agents share data from the NOAA Tides & Currents API with each other in AutoGen?

Yes. When one agent calls a tool like getwatertemperature, the result is posted into the shared conversation. Other agents can then read that output and use it in their own reasoning, allowing them to build on each other's findings.

Q: Does this MCP tool work with the standard AutoGen setup?

It does. You use the mcpservertools function from the autogen-ext library to load the NOAA tools. Then you just pass that tool list into your AssistantAgent configuration like any other function.

Use AutoGen to build teams of AI agents that debate and decide on actions using live NOAA tidal and current data.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect NOAA Tides & Currents API MCP to AutoGen

Create your Vinkius account to connect NOAA Tides & Currents API to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup NOAA Tides & Currents API with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Simulate a Debate Between Specialist Agents

AutoGen lets you create a conversation. Build a 'Port Operations' agent that uses `get_tide_predictions` to plan shipping schedules. Then, add a 'Safety Officer' agent that uses `get_water_levels` to check real-time channel depth. Set them to the same task and watch them debate. The Ops agent might push for an early departure, but the Safety agent will counter with live data showing the tide is lower than predicted. They'll argue until they reach a consensus based on the data from the tools.

Achieve Consensus on Complex Scenarios

This isn't just about one agent making a call. You can create a team. One agent checks `check_api_status` to ensure data is reliable. Another monitors `get_air_temperature` and `get_water_temperature`, flagging conditions that might affect sensor accuracy or vessel performance. A 'Lead' agent listens to the others and makes a final recommendation. This multi-agent approach surfaces risks that a single agent might miss, giving you a more resilient system for making decisions with this MCP Server.

Integrate Human Oversight into Agent Teams

Your AutoGen setup can work with a human in the loop. Let's say the agent team can't agree on whether a storm surge is affecting water levels. They can present their conflicting data, sourced from `get_tide_predictions` versus `get_water_levels`, to a human user. The user acts as the tie-breaker. This model is perfect for critical decisions where you want the speed of AI analysis but the final judgment of an experienced operator. AutoGen structures the conversation so the human gets a clear summary of the debate.

Setup guide

Set up NOAA Tides & Currents API MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes NOAA Tides & Currents API tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="NOAA Tides & Currents API_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent NOAA Tides & Currents API data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="NOAA Tides & Currents API_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent NOAA Tides & Currents API data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by NOAA Tides & Currents. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect NOAA Tides & Currents API now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about NOAA Tides & Currents API MCP in AutoGen

You assign different tools to different agents. For example, a 'Planner' agent gets `get_tide_predictions` and a 'Verifier' agent gets `get_water_levels`. Then you give them a shared goal, and they will use their assigned tools to debate the best course of action.

Build a risk assessment team. One agent argues for efficiency using tide predictions, while another argues for safety using real-time water levels. AutoGen facilitates the conversation between them to find a balanced, data-driven decision.

Yes. When one agent calls a tool like `get_water_temperature`, the result is posted into the shared conversation. Other agents can then read that output and use it in their own reasoning, allowing them to build on each other's findings.

It does. You use the `mcp_server_tools` function from the `autogen-ext` library to load the NOAA tools. Then you just pass that tool list into your AssistantAgent configuration like any other function.

The agent conversations, including any data returned from tools like `get_water_levels`, happen within your AutoGen environment. The Vinkius MCP Server only processes the individual tool calls, handling the station ID and parameters in a zero-trust, ephemeral runtime. The content of your agent debates is not visible to the server.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript