About io.github.grossiweb/toolroute
io.github.grossiweb/toolroute is an MCP server in the Science category: route AI agent tasks to the best MCP server and LLM, scored on 132+ real benchmark executions.
Install
claude mcp add io-github-grossiweb-toolroute -- npx -y @toolroute/sdknpx -y @toolroute/sdkThis 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.
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README
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_model": "gemini-flash-2.0",
"confidence": 0.91
}
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 |
/api/mcp |
POST (JSON-RPC) | MCP server — 16 tools |
/api/mcp |
GET (SSE) | SSE transport for MCP clients |
/api/report/model |
POST | Report model outcome |
/api/verify/model |
POST | Verify model output quality |
/api/skills |
GET | Search MCP server catalog |
/api/agents/register |
POST | Register agent identity |
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
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.