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MCP unreviewed MIT Self-run

L4 Smartroute

mcp-linux5real-l4-smartroute · by Linux5Real

Intelligent AI model routing for coding agents. Analyzes task complexity using knowledge graphs to recommend the best AI model & effort level across 80+ models from 15+ providers.

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Install

$ agentstack add mcp-linux5real-l4-smartroute

Open-source listing, not yet scanned by AgentStack. Follow the source repository for install instructions.

Security review

⚠ Flagged

1 finding(s); flagged for manual review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures
  • high Pipes remote content directly into a shell (remote code execution).

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Reliability & compatibility

Not yet reviewed
0 installs to date
no reviews yet
2mo ago

Declared compatibility

Claude CodeClaude DesktopCursorWindsurf

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

L4-Smartroute

Intelligent AI model routing for coding agents. Picks the right model for the right task - so you stop overpaying for simple fixes and underpowering complex refactors.

made by linux5real

What is L4-Smartroute?

L4-Smartroute is an MCP server that analyzes your task (prompt or git diff), calculates code complexity using knowledge graph analysis, and recommends the best AI model + effort level. Instead of always using the most expensive model, it routes each task to the most appropriate one from 80+ AI-models (Coding-Models) across 15 providers.

Built on Graphify

L4-Smartroute uses Graphify knowledge graphs to calculate blast radius - how many files, communities, and code paths a change affects. This drives complexity scoring and ensures high-risk cross-module work gets a capable model while simple edits stay cheap.

Features

  • 54+ models across 14 providers (Anthropic, OpenAI, Google, xAI, Meta, and more)
  • 3 router modes: deterministic, hybrid, ai-review
  • 4 optimization levels: quality, balanced, performance, token-saver
  • Graphify-powered blast radius analysis for accurate complexity scoring
  • Web UI for configuration on http://localhost:6639
  • One-command install with auto Claude Code integration

Prerequisites

  • Python 3.11+
  • One of: uv, pipx, or pip
  • Claude Code CLI (optional — for automatic MCP server registration)
  • Graphify (optional — for full blast radius analysis, run graphify ./your-project)

Installation

One Command

curl -fsSL https://raw.githubusercontent.com/Linux5Real/L4-Smartroute/main/install.sh | bash

This auto-detects your package manager (uv > pipx > pip), clones the repo locally, installs it editable, installs the Claude Code commands, and registers Claude Code with the actual installed MCP executable path.

Manual

git clone https://github.com/Linux5Real/L4-Smartroute.git
cd L4-Smartroute
pip install -e .
claude mcp add l4-smartroute -- "$(command -v l4-smartroute)"

From Source

git clone https://github.com/Linux5Real/L4-Smartroute.git
cd L4-Smartroute
pip install -e .

Setup

Start the configuration UI:

l4-smartroute-setup

This opens http://localhost:6639 where you can:

  • Select which models are available
  • Choose optimization mode (Quality / Balanced / Performance / Token Saver)
  • Set router mode (Deterministic / Hybrid / AI Review)
  • Configure Graphify path and budget settings

Claude Code Commands

  • /smartroute — Get a model recommendation for your current task
  • /smartroute-settings — Open the configuration UI

How It Works

Prompt / Git Diff
  -> Graphify blast radius (files, communities, centrality)
  -> Task classification (13 task types)
  -> Candidate scoring (fit, tier, cost, speed)
  -> Optional AI review (hybrid/ai-review mode)
  -> Final model + effort level + budget alternative

Supported Models

| Provider | Models | |----------|--------| | Anthropic | Claude Fable 5, Opus 4.8, Opus 4.7, Opus 4.6, Sonnet 4.6 / 4.5, Haiku 4.5 | | OpenAI | GPT-5.5, GPT-5.5 Pro, GPT-5.4, GPT-5.4 mini/nano, GPT-5.3 Codex, GPT-5.2 | | Google | Gemini 3.1 Pro, 3.5 Flash, 3.1 Flash-Lite, 3 Deep Think, 2.5 Pro / flash | | xAI | Grok 4.3, Grok 4.20, Grok 4.1, Grok-build-0.1 | | Meta | Llama 4 Maverick, Llama 4 Scout | | Alibaba | Qwen3.7 Max/Plus, Qwen3.6 Plus, Qwen3.5, Qwen3 Coder Next, and more | | Mistral | Mistral Large 3, Medium 3.5, Small 4 | | DeepSeek | DeepSeek V4 Pro, V4 Flash and more | | NVIDIA | Nemotron 3 Ultra, Super, Nano Omni | | Moonshot | Kimi K2.6, Kimi K2.5| | MiniMax | MiniMax-M3, M2.7, M2.5, M2.1, M2 | | Xiaomi | MiMo-V2.5-Pro, V2.5, V2-Omni, V2-Flash | | Zhipu AI | GLM-5.1, GLM-5-Turbo and more | | Others | Command A/A+, Step 3.7 Flash, KAT-Coder-Pro V2, Hy3 |

Missing a model? Open an issue and we'll add it.

License

MIT

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.