What does 'potentially hazardous' mean?

A Potentially Hazardous Asteroid (PHA) passes within 0.05 AU (~7.5 million km) and is larger than 140 meters. This doesn't mean it will hit Earth — just that its orbit warrants monitoring.

How frequently is the asteroid data updated?

The NeoWs API is updated daily with the latest orbital calculations and close approach tracking data from JPL's Center for Near Earth Object Studies.

Does this API include data on historical asteroid impacts?

Yes, the API provides access to fireball and bolide data, which tracks bright atmospheric meteor events detected by government sensors, including historical records.

NASA Asteroids — Near-Earth Objects & Planetary Defense MCP Server for CrewAI 5 tools — connect in under 2 minutes

Name: NASA Asteroids — Near-Earth Objects & Planetary Defense
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 5 Tools Framework

Connect your CrewAI agents to NASA Asteroids — Near-Earth Objects & Planetary Defense through the Vinkius — pass the Edge URL in the `mcps` parameter and every NASA Asteroids — Near-Earth Objects & Planetary Defense tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="NASA Asteroids — Near-Earth Objects & Planetary Defense Specialist",
    goal="Help users interact with NASA Asteroids — Near-Earth Objects & Planetary Defense effectively",
    backstory=(
        "You are an expert at leveraging NASA Asteroids — Near-Earth Objects & Planetary Defense 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 NASA Asteroids — Near-Earth Objects & Planetary Defense "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 5 available tools "
        "and what they can do."
    ),
)

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

NASA Asteroids — Near-Earth Objects & Planetary Defense

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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 NASA Asteroids — Near-Earth Objects & Planetary Defense MCP Server

Complete asteroid intelligence from NASA's NeoWs API and JPL's Center for Near Earth Object Studies (CNEOS).

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

What you can do

NEO Feed — Asteroids making close approaches this week
Asteroid Details — Size, orbit, velocity, hazard assessment
Close Approaches — Future Earth encounters from CNEOS
Fireballs — Atmospheric impacts detected by sensors
Browse Catalog — Paginated access to all known NEOs

The NASA Asteroids — Near-Earth Objects & Planetary Defense MCP Server exposes 5 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 NASA Asteroids — Near-Earth Objects & Planetary Defense to CrewAI via MCP

Follow these steps to integrate the NASA Asteroids — Near-Earth Objects & Planetary Defense 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 5 tools from NASA Asteroids — Near-Earth Objects & Planetary Defense

Why Use CrewAI with the NASA Asteroids — Near-Earth Objects & Planetary Defense MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with NASA Asteroids — Near-Earth Objects & Planetary Defense 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 the 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

NASA Asteroids — Near-Earth Objects & Planetary Defense + CrewAI Use Cases

Practical scenarios where CrewAI combined with the NASA Asteroids — Near-Earth Objects & Planetary Defense MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries NASA Asteroids — Near-Earth Objects & Planetary Defense 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 NASA Asteroids — Near-Earth Objects & Planetary Defense, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain NASA Asteroids — Near-Earth Objects & Planetary Defense 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 NASA Asteroids — Near-Earth Objects & Planetary Defense against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

NASA Asteroids — Near-Earth Objects & Planetary Defense MCP Tools for CrewAI (5)

These 5 tools become available when you connect NASA Asteroids — Near-Earth Objects & Planetary Defense to CrewAI via MCP:

get_close_approaches

Filter by distance threshold, date range, and minimum size. Critical for planetary defense monitoring. Get future close approaches of asteroids to Earth from JPL CNEOS

get_fireballs

Includes location, velocity, energy (kilotons of TNT equivalent), and altitude. Covers events worldwide. Get atmospheric fireball (bolide) events detected by US government sensors

get_neo_browse

Returns 20 asteroids per page. Use for exploring the complete known catalog of near-Earth objects. Browse the complete catalog of known near-Earth asteroids

get_neo_feed

Includes estimated diameter, velocity, miss distance, and whether potentially hazardous. Source: NASA NeoWs. Get near-Earth asteroids approaching within a date range

get_neo_lookup

Use SPK-IDs from the feed endpoint. Get detailed information about a specific asteroid by its NASA SPK-ID

Example Prompts for NASA Asteroids — Near-Earth Objects & Planetary Defense in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with NASA Asteroids — Near-Earth Objects & Planetary Defense immediately.

"What asteroids are passing near Earth this week?"

"Are there any large asteroids approaching Earth next month?"

"Tell me about the recent fireball detected over the Pacific."

Troubleshooting NASA Asteroids — Near-Earth Objects & Planetary Defense MCP Server with CrewAI

Common issues when connecting NASA Asteroids — Near-Earth Objects & Planetary Defense 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

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

NASA Asteroids — Near-Earth Objects & Planetary Defense + CrewAI FAQ

Common questions about integrating NASA Asteroids — Near-Earth Objects & Planetary Defense 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.