llm9p
Enables Unix-native integration of LLM capabilities into existing build pipelines and shell workflows without custom APIs or middleware, reducing integration…
LLM exposed as a 9P filesystem
- Access Claude through file system commands without rewriting application code
- Integrate language model capabilities into existing Unix tools and scripts
- Query Claude API using standard read/write operations on mounted directories
Enables Unix-native integration of LLM capabilities into existing build pipelines and shell workflows without custom APIs or middleware, reducing integration friction and operational complexity.
Infrastructure teams and DevOps engineers embedding LLM reasoning into automated scripts and system tooling.
https://github.com/NERVsystems/llm9p
By NERVsystems
How to Get It
claude plugins install NERVsystems/llm9p
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me access Claude through file system commands without rewriting application code
Trust Signals Auto-scanned
Community Pulse Emerging
Discussed on Hacker News
- Llm9p: LLM as a Plan 9 file system — Hacker News · 17 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 45 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 45 GitHub stars; contributors unknown; last commit 0d ago; license MIT.