How to Use the NASA MCP in LlamaIndex

Q: How do I configure the NASA MCP Server with LlamaIndex?

Install llama-index-tools-mcp. Use BasicMCPClient to connect to the endpoint, wrap it in an McpToolSpec, and pass the async tool list to your FunctionAgent.

Q: Can LlamaIndex store the results from NASA image searches?

Yes. When your agent calls searchnasalibrary, it takes the returned descriptions and center information, embeds them, and stores them in your vector database for future retrieval.

Q: Does the integration support filtering which tools the agent sees?

You apply the allowedtools filter during setup. This restricts the agent to only seeing getmarsphotos and ignores the patent endpoints if you are building a purely visual RAG app.

Index live space data and patents directly into your LlamaIndex knowledge base.

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Create your Vinkius account to connect NASA to LlamaIndex 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 with LlamaIndex

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Perplexity

Embed aerospace patent records

Calling `search_patents` through LlamaIndex turns raw aerospace records into a queryable vector store. You pull down abstracts for propulsion technology and immediately embed them for semantic search. This stops your AI from hallucinating orbital facts. When a user asks about licensing availability, the agent checks the actual indexed output from the MCP Server instead of guessing based on outdated training weights.

Ground your LlamaIndex RAG application

Integrating `get_neo_feed` lets your RAG pipeline ingest daily asteroid velocities and diameters. The agent fetches a seven-day window of near-Earth objects and indexes the threat assessments alongside your internal documents. You build applications where live API data merges with static text. If an engineer asks about planetary defense, the system cross-references yesterday's asteroid count with your uploaded policy PDFs.

Index visual metadata

Running `get_epic_images` via the MCP Server allows your agent to index acquisition times and coordinates for Earth imagery. It grabs the JSON response and stores the natural-color image URLs as structured nodes in your graph. Researchers then run natural language queries against this metadata. Instead of writing custom API wrappers, they just ask the index to find all polychromatic camera shots taken over specific longitudes last month.

Setup guide

Set up NASA MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all NASA MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to NASA tools.",
)
response = await agent.run("List recent NASA data")

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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 MCP in LlamaIndex

Install `llama-index-tools-mcp`. Use `BasicMCPClient` to connect to the endpoint, wrap it in an `McpToolSpec`, and pass the async tool list to your `FunctionAgent`.

Yes. When your agent calls `search_nasa_library`, it takes the returned descriptions and center information, embeds them, and stores them in your vector database for future retrieval.

Indexing provides semantic search capabilities. You fetch a massive batch of rover data once, and users ask complex questions against that specific dataset without hitting rate limits.

You apply the `allowed_tools` filter during setup. This restricts the agent to only seeing `get_mars_photos` and ignores the patent endpoints if you are building a purely visual RAG app.

This integration touches longitude coordinates, search strings, and date ranges. Every request routes through a zero-trust architecture, ensuring your specific queries never leak into persistent storage or training logs.

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