NASA-MCP-server — not yet audited

Last updated: 2026-07-04 · Indexed by AgentSkillsHub · Auto-synced every 8h

About NASA-MCP-server

A Model Context Protocol (MCP) server for NASA APIs, providing a standardized interface for AI models to interact with NASA's vast array of data sources.

Quick Facts

Stars	92
Forks	18
Language	TypeScript
Category	MCP Server
License	ISC
Quality Score	55.4636063085348/100
Last Updated	2026-07-04
Created	2025-03-06
Platforms	mcp, node
Est. Tokens	~13k

Compatible Skills

These tools work well together with NASA-MCP-server for enhanced workflows:

datafoundry — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)
monoid — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)
midi-mcp-server — semantic(0.45)+same_lang+similar_pop+shared_platform (51%)
square-mcp-server — semantic(0.44)+same_lang+similar_pop+shared_platform (50%)
computer-use-mcp — semantic(0.40)+same_lang+similar_pop+shared_platform (49%)

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Frequently Asked Questions

What is NASA-MCP-server?

NASA-MCP-server is A Model Context Protocol (MCP) server for NASA APIs, providing a standardized interface for AI models to interact with NASA's vast array of data sources.. It is categorized as a MCP Server with 92 GitHub stars.

What programming language is NASA-MCP-server written in?

NASA-MCP-server is primarily written in TypeScript.

How do I install or use NASA-MCP-server?

You can find installation instructions and usage details in the NASA-MCP-server GitHub repository at github.com/ProgramComputer/NASA-MCP-server. The project has 92 stars and 18 forks, indicating an active community.

What license does NASA-MCP-server use?

NASA-MCP-server is released under the ISC license, making it free to use and modify according to the license terms.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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