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MCP server · AI

Llmc

One stop shop - Local-first RAG stack with intelligent polyglot-code/docs, remote code execution, local llama enrichment, progressive disclosure tools, mcp server, sandboxed security.

61Good

Scored yesterday · breakdown

About Llmc

Llmc is an MCP server published by vmlinuzx in the AI category: one stop shop - Local-first RAG stack with intelligent polyglot-code/docs, remote code execution, local llama enrichment, progressive disclosure tools, mcp server, sandboxed security. It has been installed 0 times through Conduid.

The repository has 31 stars and 4 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx llmc

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

Ask AI about Llmc

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I know everything about Llmc. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

  • ·README presentNot checked yet.
  • ·License declaredNot checked yet.
  • ·Tests presentNot checked yet.
  • ·Dependencies pinnedNot checked yet.
  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v2.0.0-alpha.1v2.0.0-alpha.1
v0.8.0v0.8.0
v0.6.4v0.6.4
v0.5.5v0.5.5
v0.5.0v0.5.0

README

LLMC: Large Language Model Compressor

Stop burning money on LLM tokens. Get 70-95% cost reduction through local RAG, intelligent routing, and containerized security.

Python License Tests


⚡ What is LLMC?

LLMC is a local-first RAG (Retrieval Augmented Generation) engine and intelligent router designed to drastically reduce the cost of using Large Language Models with your codebase.

Instead of sending your entire codebase to Claude or GPT-4, LLMC indexes your code locally, finds the exact relevant snippets (functions, classes, docs), and sends only what matters.

graph LR
    A[User Query] --> B(LLMC Router);
    B --> C{Local Index};
    C -->|Search| D[Relevant Context];
    D -->|Trim & Pack| E[Optimized Prompt];
    E --> F[LLM API];
    F --> G[Answer];
    style B fill:#f9f,stroke:#333,stroke-width:2px
    style E fill:#bfb,stroke:#333,stroke-width:2px

🚀 Quick Start

Get up and running in seconds.

1. Install

# One-line install
curl -sSL https://raw.githubusercontent.com/vmlinuzx/llmc/main/install.sh | bash

# Or via pip
pip install "git+https://github.com/vmlinuzx/llmc.git#egg=llmcwrapper[rag,tui,agent]"

2. Index Your Code

cd /path/to/your/project
llmc-cli repo register .

3. Save Money

# Search without using ANY tokens
llmc-cli search "authentication middleware"

# Launch the visual dashboard
llmc-cli tui

✨ Key Features

Feature Description
💸 Massive Savings Reduces token usage by 70-95% by sending only relevant context.
🔒 Security First New in v0.7.0: "Hybrid Mode" for trusted clients (host access) vs. Container Isolation for untrusted LLMs.
🧠 Polyglot RAG Smart parsing (TreeSitter) for Python, TS, JS, Go, Java, and technical docs.
🕸️ GraphRAG Understands your code structure (imports, calls, inheritance) to find related files automatically.
🖥️ TUI Dashboard Terminal UI to monitor indexing, search results, and costs. ⚠️ Work in progress — expect rough edges.
🔌 MCP Support Full Model Context Protocol server to integrate seamlessly with Claude Desktop.

🔍 Deep Dive

  • Local SQLite Index: Stores text + metadata without external dependencies.
  • Smart Embeddings: Caches embeddings to avoid re-computing unchanged files.
  • Context Trimmer: Packs the most relevant spans into a fixed token budget.
  • Enrichment: Uses small local models to tag and summarize code for better retrieval.
  • Hybrid Mode: Trusted clients get direct host access (~76% cheaper than docker overhead).
  • Container Isolation: Untrusted inputs run in Docker/nsjail.
  • Defense in Depth: Even if an LLM is "jailbroken" by prompt injection, it can't escape the container.
  • Intelligent Failover: Cascades from Local → Cheap Cloud → Premium Models.
  • Cost Tracking: Hard budget caps to prevent surprise bills.
  • Rate Limiting: Automatic token bucket throttling for API providers.

📚 Documentation

Full documentation is available in the DOCS/ directory:


📜 History

Originally created by David Carroll (the worst paragliding pilot in the TX Panhandle) after burning through his weekly API limits in days. This tool was born from the necessity to code more while spending less.


🤝 Contributing

We welcome PRs! Please check CONTRIBUTING.md before starting.

  1. Fork the repo
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Current Release: v0.9.1 "Back From Vacation"

README mirrored from the source repository yesterday. The original is authoritative.

Questions

About Llmc

How do I install Llmc?

Run npx llmc, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Llmc safe to use with an AI agent?

Its trust score is 61 out of 100 (good). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Llmc still maintained?

The last commit was 6 months ago, with 0 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.