Borrowing it
Nothing to install: this file belongs to georgepok/local-llm-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/georgepok/local-llm-mcp-server/main/CLAUDE.mdgit clone --depth 1 https://github.com/georgepok/local-llm-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/georgepok/local-llm-mcp-server/claude-md)<a href="https://agentmods.dev/instructions/georgepok/local-llm-mcp-server/claude-md"><img src="https://agentmods.dev/badge/instructions/georgepok/local-llm-mcp-server/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/georgepok/local-llm-mcp-server/claude-md"><img src="https://agentmods.dev/badge/instructions/georgepok/local-llm-mcp-server/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01658 | $0.01658 |
| Opus 5 | $0.00829 | $0.00829 |
| Sonnet 5 | $0.00332 | $0.00332 |
| Haiku 4.5 | $0.00166 | $0.00166 |
Grade A, and why
local-llm-mcp-server CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Code Project Guide
What This Is
A monorepo combining a production MCP server with six research subprojects exploring geometric neural networks, continuous-time ODE models, and ARC-AGI solving — all targeting NVIDIA DGX Spark (GB10, 128GB unified memory).
Repository Structure
local-llm-mcp-server/
├── src/ # Production MCP server (TypeScript/Node.js)
├── config.json # MCP server config (points to DGX Spark vLLM)
├── subprojects/
│ ├── fluid-geometry/ # vLLM logits processor — entropy-driven reasoning control
│ ├── fgn-v3/ # Fluid Geometry Network — Riemannian attention replacement
│ ├── liquid-arc/ # LiquidARC — continuous-time geometric ODE for ARC-AGI
│ ├── latent-oracle/ # Oracle embedding distillation via HyperNet
│ ├── neuroplastic/ # Self-introspecting neural substrate (Nemotron)
│ └── wake-sleep/ # Autonomous wake-sleep training loop
Subproject Relationships
The subprojects form a research progression:
-
fluid-geometry — Production plugin. Single-file vLLM LogitsProcessor that adapts temperature and thinking tokens based on entropy curvature. Deployed on DGX Spark.
-
fgn-v3 — Foundation research. Replaces transformer dot-product attention with diffusion on learned Riemannian manifold. Heat kernel attention via geodesic distances. This is the theoretical basis for LiquidARC.
-
liquid-arc — Primary research project. Clean-slate continuous-time ODE model where geometry IS the computation. One shared dynamics module applied 16x via Euler integration. SDPA-factored heat kernel enables FlashAttention. Key results:
- Phase transition at CV~6.0 produces universal geometric substrate
- Geometry distillation: 71% eval ARC (vs teacher's 54%), 72% graph coloring
- 100x geometric LR ratio is the critical training insight
-
latent-oracle — Distillation. Uses oracle model (Qwen3.5-9B) embeddings as task descriptors to predict task-specific weight deltas via HyperNet.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 145 lines · 1,658 tokens per session scan A 91ae9e5c76b5
local-llm-mcp-server CLAUDE.md is an instructions file published in the GitHub repository georgepok/local-llm-mcp-server (0 stars, last pushed 1mo ago), licensed MIT. It adds 1,658 tokens to every session, about $0.0083 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-01.
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