Toolroute

Name: Toolroute
Author: grossiweb

by grossiwebversion 0.2.2i★ –iRuns on your computer

Registry nameio.github.grossiweb/toolroute

Install

Overview

Description from the maker (original English)

Route AI agent tasks to the best MCP server and LLM, scored on 132+ real benchmark executions.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "toolroute": {
      "command": "npx",
      "args": [
        "-y",
        "@toolroute/sdk"
      ]
    }
  }
}

Run this in your terminal

claude mcp add toolroute -- npx -y @toolroute/sdk

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "toolroute": {
      "command": "npx",
      "args": [
        "-y",
        "@toolroute/sdk"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "toolroute": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@toolroute/sdk"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account grossiweb, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7266 servers in this category
Published to the registry more recently than 7% of the other 7266 servers in this category
Basic checks equal to or better than 100% of the other 7266 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Toolroute safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.2) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

ToolRoute

Routing layer for AI agents. One call returns the best MCP server and LLM for any task — scored on 132 real benchmark executions.

Quick start

Add to any MCP client (Claude Code, Cursor, Windsurf, Cline):

"mcpServers": { "toolroute": { "url": "https://toolroute.io/api/mcp" } } }

Or via HTTP:

curl -X POST https://toolroute.io/api/route \

-H "Content-Type: application/json" \ -d '{"task": "search the web for recent AI papers"}'

"approach": "mcp_server", "recommended_skill": "exa-mcp-server", "recommended_skill_name": "Exa MCP Server", "recommended_model": { "slug": "claude-haiku-4-5-20251001", "display_name": "Claude Haiku 4.5", "provider": "anthropic", "tier": "cheap_chat", "provider_model_id": "anthropic/claude-haiku-4-5-20251001", "input_cost_per_mtok": 1.00, "output_cost_per_mtok": 5.00 }, "confidence": 0.91, "alternatives": ["brave-search-mcp", "tavily-mcp"], "fallback": "brave-search-mcp" }

recommended_model is always an object, not a bare string — the inner slug is the canonical model identifier.

How it works

Every task falls into one of three approaches:

Approach	When	Returns
`direct_llm`	Task needs only an LLM (code, writing, analysis)	Best model + cost estimate
`mcp_server`	Task needs an external tool (search, email, calendar)	Best tool + best model
`multi_tool`	Compound task ("send Slack AND update Jira AND email")	Ordered orchestration chain

Routing uses an LLM classifier (~$0.00001/call) for task understanding, then ranks candidates on a 5-dimension score:

Value Score = 0.35 × Output Quality

0.25 × Reliability
0.15 × Efficiency
0.15 × Cost
0.10 × Trust

Every reported outcome updates the scores. The routing gets more accurate as more agents use it.

Benchmark results

132 blind A/B executions across code, writing, analysis, structured output, and translation.

	ToolRoute	Fixed GPT-4o
Quality wins	6	0
Ties	9	9
Losses	0	—
Avg cost	$0.001–0.01	$0.03–0.10

API

Endpoint	Method	Description
`/api/route`	POST	Route a task to best MCP server + LLM (unified)
`/api/route/model`	POST	Route to best LLM model only (no MCP server)
`/api/mcp`	POST (JSON-RPC)	MCP server — 16 tools
`/api/mcp`	GET (SSE)	SSE transport for MCP clients
`/api/report`	POST	Report MCP server outcome (lightweight)
`/api/contributions`	POST	Advanced MCP skill telemetry (requires `skill_id` or `skill_slug` in payload)
`/api/report/model`	POST	Report LLM model outcome — use this for model telemetry, not `/api/contributions`
`/api/verify/model`	POST	Verify model output quality
`/api/skills`	GET	Search MCP server catalog
`/api/agents/register`	POST	Register agent identity
`/api/agents/preferences`	POST	Set routing preferences (Strategy D Phase 2 — `allow_china`, `regulated_industries`)
`/api/health`	GET	Service health check (DB + uptime)
`/api/metrics`	GET	Public aggregate platform metrics (no auth)

Full reference at toolroute.io/api-docs

SDK

npm install @toolroute/sdk

import { ToolRoute } from '@toolroute/sdk'

const tr = new ToolRoute() const rec = await tr.route({ task: 'parse this CSV and summarize it' }) // execute with rec.recommended_model ... await tr.report({ skill: rec.recommended_skill, outcome: 'success', latency_ms: 1400 })

Self-hosting

git clone https://github.com/grossiweb/ToolRoute.git

cd ToolRoute cp .env.local.example .env.local npm install npm run dev

Requires: NEXT_PUBLIC_SUPABASE_URL, NEXT_PUBLIC_SUPABASE_ANON_KEY, SUPABASE_SERVICE_ROLE_KEY

How routing works

ToolRoute classifies each task using an LLM classifier (Gemini Flash Lite, ~$0.00001/call) with a keyword fallback. The resulting tier maps to a specific model via src/lib/routing/tiers.ts. Live pricing and capability data come from the models table. See docs/architecture.md for the full picture.

Stack

Next.js 14 (App Router) · Supabase (Postgres) · Vercel

License

MIT

Toolroute

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

ToolRoute

Quick start

How it works

Benchmark results

API

SDK

Self-hosting

How routing works

Stack

License