Where do I retrieve my Tomorrow.io API Key?

Log into your account via `app.tomorrow.io`. Navigate directly to the **API Management** or Developer tab nested inside your settings. Create a new root token, copy it in its entirety, and insert it securely to enable queries.

How accurate is the 'minutely' precipitation forecast tool?

Tomorrow.io operates proprietary radar networks, satellites, and sophisticated high-resolution systems natively intended to provide powerful precision for up to exactly 60 minutes ahead, projecting precipitation downshifts incredibly well locally.

How far into the future can the agent forecast extreme weather events?

Using Tomorrow.io's advanced predictive modeling, the agent can provide precise hour-by-hour projections and daily forecasts up to 15 days ahead. This extended timeline offers ample opportunity for logistical and operational planning against severe environmental risks.

Tomorrow.io MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Tomorrow.io
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Tomorrow.io through Vinkius, pass the Edge URL in the `mcps` parameter and every Tomorrow.io 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

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Tomorrow.io Specialist",
    goal="Help users interact with Tomorrow.io effectively",
    backstory=(
        "You are an expert at leveraging Tomorrow.io 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 Tomorrow.io "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Tomorrow.io MCP Server

Connect your Tomorrow.io account to any AI agent and integrate institutional-grade weather modeling into your logic flows. Retrieve hyperlocal conditions, predict rainfall down to the specific minute, and access specialized environmental matrices (air quality, fire risks, and ground road weather) directly through natural language queries.

When paired with CrewAI, Tomorrow.io becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Tomorrow.io 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

Real-time Observations — Check comprehensive atmospheric indicators for any latitude, longitude, city, or zip code dynamically
Interval Forecasting — Read forward-looking timelines segmented by minute (precipitation), hours (daily events), or deep daily projections up to 15 days out
Environmental Hazards — Interrogate the AQI (Air Quality Index), pollen density predictions, or active Wildfire index algorithms
Logistical Safeguards — Check specialized Road Risk parameters natively, enabling safer fleet routing algorithms against complex weather patterns
Historical Auditing — Query observed historical conditions by defining past temporal boundaries and desired weather field sets for retroactive analysis

The Tomorrow.io MCP Server exposes 10 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 Tomorrow.io to CrewAI via MCP

Follow these steps to integrate the Tomorrow.io 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 10 tools from Tomorrow.io

Why Use CrewAI with the Tomorrow.io MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Tomorrow.io 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

Tomorrow.io + CrewAI Use Cases

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

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

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

Tomorrow.io MCP Tools for CrewAI (10)

These 10 tools become available when you connect Tomorrow.io to CrewAI via MCP:

get_air_quality_index

Retrieve current and forecast air quality data

get_custom_timelines

Query weather data for custom time ranges and arbitrary intervals

get_daily_forecast

Returns up to 15 days of daily intervals. Retrieve daily weather forecast extremes and totals

get_historical_weather

Retrieve actual recorded historical weather observations

get_hourly_forecast

Returns up to 120 hours of predictions. Retrieve hour-by-hour weather forecast for a location

get_minutely_precipitation

Retrieve minute-by-minute precipitation nowcast

get_pollen_forecast

Retrieve daily pollen count indices

get_realtime_weather

Provide a location (lat,lon, city name, or zip) and field list. Retrieve current real-time weather conditions for any global location

get_road_weather_risk

Retrieve assessments for driving and road hazards

get_wildfire_risk

Retrieve wildfire risk index and weather conditions

Example Prompts for Tomorrow.io in CrewAI

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

"What is the expected air quality index in New York over the next hour?"

"Show me the minute-by-minute precipitation near Golden Gate bridge right now."

Troubleshooting Tomorrow.io MCP Server with CrewAI

Common issues when connecting Tomorrow.io 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.

Tomorrow.io + CrewAI FAQ

Common questions about integrating Tomorrow.io 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.