Server data from the Official MCP Registry
Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.
Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.
Remote endpoints: streamable-http: https://local-model-suitability-mcp-production.up.railway.app
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
1 tool verified · Open access · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: ANTHROPIC_API_KEY
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
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.
check_local_viabilityCall 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:
| Field | Required | Description |
|---|---|---|
task | ✅ | The exact task you are about to send to a cloud model |
quality_threshold | Optional | PRODUCTION (default) / PROTOTYPE / BEST_EFFORT |
data_sensitivity | Optional | PUBLIC (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"
}
| Plan | Calls | Price |
|---|---|---|
| Free | 20/month | $0 |
| Starter | 500-call bundle | $20 |
| Pro | 2,000-call bundle | $70 |
{
"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.
{
"mcpServers": {
"local-model-suitability": {
"type": "http",
"url": "https://local-model-suitability-mcp-production.up.railway.app"
}
}
}
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()
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"
})]
)
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
Be the first to review this server!
by Modelcontextprotocol · Developer Tools
Web content fetching and conversion for efficient LLM usage
by Modelcontextprotocol · Developer Tools
Read, search, and manipulate Git repositories programmatically
by Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.