How to Use the NASA Open Data MCP in LangChain

Build autonomous chains with LangChain that react to real-time NASA space data feeds.

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Connect NASA Open Data MCP to LangChain

Create your Vinkius account to connect NASA Open Data to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup NASA Open Data with LangChain

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Chain NASA API Calls Together

Create agents that sequence NASA tools. You can build a chain that first calls `get_near_earth_objects_feed` to get a list of today's asteroids, then automatically loops through them, passing each ID to `lookup_asteroid` for detailed analysis. The agent decides the next step based on the data it gets back. This isn't just a simple script. LangSmith gives you full visibility into every step, showing you the inputs, outputs, and latency for each tool call. Your agent can combine this NASA MCP Server with other tools, like a vector database or a messaging API, to build a complete, observable pipeline.

Automate Space Weather Monitoring

Let your agent monitor space weather for you. It can be configured to periodically call `get_solar_flares` and `get_coronal_mass_ejections`, parsing the results to check for events that meet specific criteria you define. No more manually checking dashboards. When your agent finds a significant event, the chain doesn't have to stop there. It can then use other tools to send a notification, log the event to a database, or even trigger another process. It's about building automated responses, not just fetching data.

Explore Mars and the Cosmos with LangChain

Build a research agent that pulls images and data on demand. Start by getting the mission details with `get_mars_rover_manifest`, then use that information to intelligently query for specific images using `get_mars_rover_photos`. Your agent can even fetch the `get_astronomy_picture` of the day. Because LangChain handles the reasoning, you don't have to hardcode every single step. Just give the agent the tools and a goal, like "find the most recent photo from Curiosity's Mast Cam." It will figure out the right sequence of tool calls to get the job done.

Setup guide

Set up NASA Open Data MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes NASA Open Data tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "nasa-open-data-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent NASA Open Data transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by NASA. 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.

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Common questions about NASA Open Data MCP in LangChain

You pass the tools from this MCP server to a LangChain agent. The agent can then use `get_near_earth_objects_feed` to find asteroids and `lookup_asteroid` to get specifics on each one, all within a single reasoning chain.

Yes. Your LangChain agent can hold tools from this server and any other source. For example, you could use `get_solar_flares` and then use a separate tool to send a Slack message if a flare is above a certain class.

Absolutely. LangSmith provides full tracing for every tool call. You can see the exact data passed to tools like `get_mars_rover_photos` and what the NASA API returned, which is critical for debugging your agent's logic.

An agent can make decisions. Instead of just fetching a list of CMEs with `get_coronal_mass_ejections`, an agent can analyze the list, decide which ones are significant, and take further action without you pre-defining every possible path.

This server only processes public NASA telemetry data, like asteroid orbital parameters and space weather logs. Vinkius isolates each request in an ephemeral sandbox, and your MCP endpoint token is the only credential needed. No personal data is ever involved.

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