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Local Model Suitability MCP

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Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.

Code source Site web Documentation

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http local-model-suitability-mcp 'https://local-model-suitability-mcp-production.up.railway.app'
Configuration JSON (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "local-model-suitability-mcp": {
            "type": "http",
            "url": "https://local-model-suitability-mcp-production.up.railway.app"
        }
    }
}
NPM package local-model-suitability-mcp
Claude Code 
claude mcp add local-model-suitability-mcp -e 'ANTHROPIC_API_KEY=<your anthropic_api_key>' -- npx -y local-model-suitability-mcp@1.1.23
Configuration JSON (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "local-model-suitability-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "local-model-suitability-mcp@1.1.23"
            ],
            "env": {
                "ANTHROPIC_API_KEY": "<your anthropic_api_key>"
            }
        }
    }
}

Variables d'environnement

  • ANTHROPIC_API_KEY obligatoire secret Anthropic API key for Claude routing analysis

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Local Model Suitability MCP
  2. The Tool
  3. Data Sources
  4. Pricing
  5. Setup
  6. Harness Integration
  7. Legal

Local Model Suitability MCP

Cloud inference is expensive. Everything that can run locally should.

This MCP server tells your agent — before every cloud API call — whether the task can be handled by a local model instead. Route to Ollama, LM Studio, or llama.cpp when you can. Only pay for cloud when you must.

The Tool

check_local_viability

Call this BEFORE every cloud inference call. If verdict is LOCAL, skip the cloud call entirely and route to your local model. Only use cloud when this tool returns CLOUD.

Inputs:

FieldRequiredDescription
task✅The exact task you are about to send to a cloud model
quality_thresholdOptionalPRODUCTION (default) / PROTOTYPE / BEST_EFFORT
data_sensitivityOptionalPUBLIC (default) / INTERNAL / CONFIDENTIAL

CONFIDENTIAL forces LOCAL regardless of task complexity — data never leaves the machine.

Response:

{
  "verdict": "LOCAL",
  "confidence": "HIGH",
  "reason": "Simple text summarisation — no reasoning depth required. Any 7B+ local model handles this well.",
  "estimated_cost_saving": "$0.002-0.008 saved per call at claude-sonnet pricing",
  "recommended_local_models": ["llama3.2:8b", "mistral-7b", "phi3:medium"],
  "cloud_justified_reason": null,
  "analysis_type": "AI-powered cost routing — NOT a simple lookup"
}

Data Sources

  • AI reasoning: Anthropic Claude (claude-sonnet) — cost routing analysis
  • No external data sources — pure AI reasoning

Pricing

PlanCallsPrice
Free20/month$0
Starter500-call bundle$20
Pro2,000-call bundle$70

Subscribe at kordagencies.com

Setup

{
  "mcpServers": {
    "local-model-suitability": {
      "command": "npx",
      "args": ["-y", "local-model-suitability-mcp"],
      "env": {
        "ANTHROPIC_API_KEY": "your-key",
        "API_KEY": "your-lms-api-key-for-paid-tier"
      }
    }
  }
}

Free tier requires no API key — tracked by IP.

Harness Integration

Claude Code / Claude Desktop (.mcp.json)
{
  "mcpServers": {
    "local-model-suitability": {
      "type": "http",
      "url": "https://local-model-suitability-mcp-production.up.railway.app"
    }
  }
}
LangChain (Python)
from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient({
    "local-model-suitability": {
        "url": "https://local-model-suitability-mcp-production.up.railway.app",
        "transport": "http"
    }
})
tools = await client.get_tools()
OpenAI Agents SDK (Python)
from agents import Agent, HostedMCPTool
agent = Agent(
    name="Assistant",
    tools=[HostedMCPTool(tool_config={
        "type": "mcp",
        "server_label": "local-model-suitability",
        "server_url": "https://local-model-suitability-mcp-production.up.railway.app",
        "require_approval": "never"
    })]
)
LangGraph

Same as LangChain above — langchain-mcp-adapters works with LangGraph natively.

Results are for cost-optimisation guidance only and do not constitute technical advice. Full terms: kordagencies.com/terms.html

Questions fréquentes

Qu'est-ce que Local Model Suitability MCP ?

Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.

Comment installer Local Model Suitability MCP ?

Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http local-model-suitability-mcp 'https://local-model-suitability-mcp-production.up.railway.app'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour Local Model Suitability MCP ?

Oui. Il attend ANTHROPIC_API_KEY, à renseigner dans sa configuration.

Local Model Suitability MCP est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Local Model Suitability MCP ?

Il est publié par OjasKord. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.