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llm9p

Skill Development Usable
Works inClaude Code
Usable Scanned — metadata only

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

46 starsMIT (commercial OK)FreeQuick setup
Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

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.

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https://github.com/NERVsystems/llm9p

By NERVsystems

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
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.

First thing to try

After installing, paste this into Claude:

Help me access Claude through file system commands without rewriting application code
CostFree

Trust Signals Auto-scanned

Stars46Contributors2Last updated2026-09-01LicenseMIT (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-09-19 · scanner v1

Community Pulse Emerging

Discussed on Hacker News

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.

How to evaluate tools before deploying →

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

Ease of Use
3/5
Versatility
2/5
Reliability
3/5
Security
3/5
Overall score2.75 / 5.00 UsableEvaluatedSep 2026
Scored from trust signals (evidence-eval-v1): 45 GitHub stars; contributors unknown; last commit 0d ago; license MIT.

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