What is the habitable zone?

The habitable zone ('Goldilocks zone') is the range of distances from a star where liquid water could exist on a planet's surface — not too hot, not too cold. We filter for equilibrium temperatures between 200-320K and rocky sizes (< 2 Earth radii).

NASA Exoplanets — Worlds Beyond Our Solar System MCP Server for Pydantic AI 4 tools — connect in under 2 minutes

Name: NASA Exoplanets — Worlds Beyond Our Solar System
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 4 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect NASA Exoplanets — Worlds Beyond Our Solar System through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

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Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to NASA Exoplanets — Worlds Beyond Our Solar System "
            "(4 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in NASA Exoplanets — Worlds Beyond Our Solar System?"
    )
    print(result.data)

asyncio.run(main())

NASA Exoplanets — Worlds Beyond Our Solar System

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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 Exoplanets — Worlds Beyond Our Solar System MCP Server

Direct SQL-like access to NASA's Exoplanet Archive — the world's most comprehensive database of confirmed planets beyond our solar system.

Pydantic AI validates every NASA Exoplanets — Worlds Beyond Our Solar System tool response against typed schemas, catching data inconsistencies at build time. Connect 4 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Search Planets — By name, method, facility, year
Transit Planets — Kepler and TESS discoveries
Habitable Zone — Rocky planets where water could exist
Statistics — Totals, methods, trends

No API Key Required

The Exoplanet Archive TAP service is completely open.

The NASA Exoplanets — Worlds Beyond Our Solar System MCP Server exposes 4 tools through the Vinkius. Connect it to Pydantic AI 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 Exoplanets — Worlds Beyond Our Solar System to Pydantic AI via MCP

Follow these steps to integrate the NASA Exoplanets — Worlds Beyond Our Solar System MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

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 4 tools from NASA Exoplanets — Worlds Beyond Our Solar System with type-safe schemas

Why Use Pydantic AI with the NASA Exoplanets — Worlds Beyond Our Solar System MCP Server

Pydantic AI provides unique advantages when paired with NASA Exoplanets — Worlds Beyond Our Solar System through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your NASA Exoplanets — Worlds Beyond Our Solar System integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your NASA Exoplanets — Worlds Beyond Our Solar System connection logic from agent behavior for testable, maintainable code

NASA Exoplanets — Worlds Beyond Our Solar System + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the NASA Exoplanets — Worlds Beyond Our Solar System MCP Server delivers measurable value.

Type-safe data pipelines: query NASA Exoplanets — Worlds Beyond Our Solar System with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple NASA Exoplanets — Worlds Beyond Our Solar System tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query NASA Exoplanets — Worlds Beyond Our Solar System and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock NASA Exoplanets — Worlds Beyond Our Solar System responses and write comprehensive agent tests

NASA Exoplanets — Worlds Beyond Our Solar System MCP Tools for Pydantic AI (4)

These 4 tools become available when you connect NASA Exoplanets — Worlds Beyond Our Solar System to Pydantic AI via MCP:

get_habitable_zone

These are the most promising candidates for life. Get exoplanets in the habitable zone — where liquid water could exist

get_planet_stats

Shows how exoplanet science has exploded since Kepler's launch in 2009. Get global exoplanet discovery statistics: totals, methods, yearly trends

get_transit_planets

Transit is the most productive method (>75% of all discoveries). Kepler and TESS are the primary transit missions. Get exoplanets discovered via the transit method (Kepler/TESS)

query_confirmed_planets

Filter by planet name, discovery method (Transit, Radial Velocity, Imaging, Microlensing), discovery facility (Kepler, TESS, Keck), or year. Returns orbital period, radius, mass, equilibrium temperature. Search confirmed exoplanets by name, discovery method, facility, or year

Example Prompts for NASA Exoplanets — Worlds Beyond Our Solar System in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with NASA Exoplanets — Worlds Beyond Our Solar System immediately.

"How many exoplanets have been discovered?"

"Show me planets in the habitable zone"

Troubleshooting NASA Exoplanets — Worlds Beyond Our Solar System MCP Server with Pydantic AI

Common issues when connecting NASA Exoplanets — Worlds Beyond Our Solar System to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

NASA Exoplanets — Worlds Beyond Our Solar System + Pydantic AI FAQ

Common questions about integrating NASA Exoplanets — Worlds Beyond Our Solar System MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your NASA Exoplanets — Worlds Beyond Our Solar System MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.