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viventine-space/orbit-sentinel-mcp

by Various

MCP server for Orbit Sentinel — space regulatory filings from FCC, ITU, UNOOSA, FAA-AST

MCP

viventine-space/orbit-sentinel-mcp

Added 3 Sept 2026

#fcc #golang #mcp #mcp-server #model-context-protocol #regulatory-data #satellite #space

Overview

MCP server for Orbit Sentinel that provides access to space regulatory filings from FCC, ITU, UNOOSA, and FAA-AST. Written in Go, it exposes these data sources through the Model Context Protocol for integration with AI assistants and other MCP clients.

Best for

Best for
Developers needing a lightweight MCP bridge to space regulatory filing data

Use cases

  • Query satellite and space launch regulatory filings across multiple agencies
  • Monitor updates to FCC, ITU, UNOOSA, and FAA-AST records programmatically
  • Integrate space regulatory data into AI-powered research or compliance tools

Notes

MCP server for Orbit Sentinel that provides access to space regulatory filings from FCC, ITU, UNOOSA, and FAA-AST. Written in Go, it exposes these data sources through the Model Context Protocol for integration with AI assistants and other MCP clients.

1 stars on GitHub. Last updated 2026-08-16. Licensed MIT.

Use cases

  • Query satellite and space launch regulatory filings across multiple agencies
  • Monitor updates to FCC, ITU, UNOOSA, and FAA-AST records programmatically
  • Integrate space regulatory data into AI-powered research or compliance tools

Pros

  • Covers multiple major space regulatory bodies in one interface
  • Go implementation offers a single binary deployment
  • MCP standard enables use with various AI assistants

Cons

  • Very early stage with minimal community adoption (1 star)
  • No evidence of active maintenance or documentation depth
  • Limited to the data sources listed; no custom agency support mentioned

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Covers multiple major space regulatory bodies in one interface
  • Go implementation offers a single binary deployment
  • MCP standard enables use with various AI assistants

Cons

  • Very early stage with minimal community adoption (1 star)
  • No evidence of active maintenance or documentation depth
  • Limited to the data sources listed; no custom agency support mentioned
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