Which integrations are available for this server?

Provides tools for discovering and ranking AI agent services, leveraging Cloudflare Workers for global edge deployment and Cloudflare D1 for database storage. Enables service discovery and ranking for AI agents, built on Cloudflare Workers runtime with D1 database and Vectorize for semantic search. Indexes and ranks DeepL translation services for AI agents, allowing discovery of best cost/quality translation tools for specific needs. Crawls and indexes services from GitHub awesome-mcp repository, enabling discovery and ranking of MCP services for AI agents. Provides REST API endpoints for service discovery and ranking using Hono framework on Cloudflare Workers. Uses OpenAI embeddings for semantic matching of service descriptions to agent needs, enabling intelligent service recommendations. Stores service metadata and call reports in Cloudflare D1 (SQLite-based database) for ranking and analytics. References Stripe MPP payment protocol as part of the AI agent ecosystem context for service discovery and ranking. Provides TypeScript SDK with full type safety for programmatic access to service discovery and ranking capabilities. Described as the "Yelp for the Agent Economy," providing ranked recommendations for AI agent services based on multiple quality dimensions.

disvr by Svanik-yan

Why Disvr?

The AI Agent ecosystem is exploding. Payment protocols (Stripe MPP, OpenAI ACP, x402) solve how to pay. Directories (Smithery, Composio) solve what exists.

But nobody solves the most critical question: which tool is actually worth using?

🤖 "Translate a Chinese legal contract to Thai" → 50 translation services on Smithery. Which one has the best cost/quality ratio?
🤖 "Scrape product prices from e-commerce sites" → 30 scraping tools. Which one has the highest success rate and lowest latency?
🤖 "Generate a product image" → 20 image generation services. Which one is cheapest while still being good enough?

Right now, agents pick blindly. Wrong picks mean wasted money, wasted time, and failed tasks.

Disvr fixes this.

Instead of returning a list, Disvr returns a ranked recommendation — based on a 4-dimensional value score:

Dimension	Weight	What it measures
🎯 Semantic Match	0.30	How well the service matches the need
⭐ Quality	0.25	Historical success rate, reputation
💰 Cost Efficiency	0.25	Cost per call, value for money
🔒 Reliability	0.20	Latency, retry rate, uptime

Your agent stops guessing and starts choosing the best tool for the job.

✅ Before You Start


💰 Free to use	Free tier: 1,000 queries/day, no credit card required
🔌 MCP Native	One-line config for Claude Code, Cursor, or any MCP client
🔄 Closed-Loop Feedback	Agents report call results → rankings get smarter over time
☁️ Global Edge	Deployed on Cloudflare Workers, low latency worldwide
📡 Real-time Data	Hourly crawls from Smithery keep service data fresh

Quick Start

Option 1: MCP Server (Recommended)

Add one line to your .mcp.json:

{
  "mcpServers": {
    "disvr": {
      "type": "url",
      "url": "https://api.disvr.top/mcp"
    }
  }
}

Restart Claude Code / Cursor — your agent now has the discover_services tool.

Try telling your agent:

"Find the best tool to translate Chinese legal documents to Thai"
"Recommend the cheapest web scraping service with high success rate"
"Which image generation API has the best price/quality ratio?"

Option 2: REST API

curl -X POST https://api.disvr.top/discover \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"need": "translate Chinese legal contract to Thai"}'

Returns Top 3 recommendations ranked by value_score:

{
  "recommendations": [
    {
      "service": "deepl-mcp-server",
      "platform": "smithery",
      "match_confidence": 0.92,
      "reputation": 4.2,
      "price_usd": 0.002,
      "reason": "Best cost/quality ratio for legal document translation"
    }
  ]
}

Live Demo

Page	Link	Description
🏠 Home	www.disvr.top	Product overview
🔍 Explorer	www.disvr.top/explorer	Interactive query playground — try the API live
📋 Registry	www.disvr.top/registry	Browse all indexed services
📊 Analytics	www.disvr.top/analytics	System architecture & scoring visualization

API Reference

`POST /discover` — Service Discovery

Describe what your agent needs, get back Top 3 ranked recommendations.

POST https://api.disvr.top/discover
Authorization: Bearer <api-key>
Content-Type: application/json

{
  "need": "scrape product prices from e-commerce websites",
  "max_price_per_call": 0.01,
  "max_latency_ms": 5000,
  "min_reputation": 3.0
}

Parameter	Required	Description
`need`	✅	What you need (≥5 chars)
`max_price_per_call`	❌	Max price per call (USD)
`max_latency_ms`	❌	Max acceptable latency (ms)
`min_reputation`	❌	Min reputation score (0-5)

`POST /report` — Feedback Loop

Report call results after using a tool — closes the feedback loop and improves rankings.

POST https://api.disvr.top/report
Authorization: Bearer <api-key>
Content-Type: application/json

{
  "service_id": "deepl-mcp-server",
  "query_id": "q_abc123",
  "success": true,
  "latency_ms": 1200,
  "cost_usd": 0.002
}

`GET /health` — Health Check

curl https://api.disvr.top/health
# {"status": "ok", "services_indexed": 330}

MCP Tools

Tools exposed via the MCP Server:

Tool	Description
`discover_services`	Semantic search + 4-dim value ranking
`list_service_count`	Total number of indexed services
`report_call_result`	Report call results (feedback loop)

SDK

TypeScript/JavaScript SDK with full type safety:

npm install @sylar_yan/disvr

import { Disvr } from "@sylar_yan/disvr";

const client = new Disvr("dsvr_your_api_key");

const result = await client.discover({
  need: "translate Chinese legal contract to Thai",
  max_latency_ms: 3000,
  min_reputation: 3.5,
});

console.log(result.recommendations);

Architecture

Agent Query ("I need X")
       │
       ▼
┌─────────────────────────────────────────┐
│  Disvr API (Cloudflare Workers + Hono)  │
├─────────────────────────────────────────┤
│                                         │
│  ┌──────────┐    ┌──────────────────┐   │
│  │ Embed    │───▶│ CF Vectorize     │   │
│  │ (OpenAI) │    │ (1536-dim cosine)│   │
│  └──────────┘    └────────┬─────────┘   │
│                           │             │
│         ┌─────── 50 candidates ──────┐  │
│         ▼                            │  │
│  ┌──────────────┐   ┌────────────┐   │  │
│  │ D1 Database  │   │ FTS5       │   │  │
│  │ (services,   │   │ (fallback) │   │  │
│  │  call_reports)│   └────────────┘   │  │
│  └──────┬───────┘                    │  │
│         │                            │  │
│         ▼                            │  │
│  ┌──────────────────────────────┐    │  │
│  │ 4-Dim Value Ranking          │    │  │
│  │ semantic × 0.30              │    │  │
│  │ quality  × 0.25              │    │  │
│  │ cost_eff × 0.25              │    │  │
│  │ reliable × 0.20              │    │  │
│  └──────────┬───────────────────┘    │  │
│             ▼                        │  │
│        Top 3 Recommendations         │  │
│                                      │  │
├──────────────────────────────────────┤  │
│  MCP Server (Streamable HTTP)        │  │
│  via CF Agents SDK + Durable Objects │  │
└──────────────────────────────────────┘  │
                                          │
       ┌──────────────────────────────────┘
       ▼
  ┌─────────────┐
  │ Cron Trigger │  ← Hourly: crawl (Smithery + GitHub + MCP Registry)
  │ (4-phase)    │     → enrich GitHub Stars → health checks
  └─────────────┘     → aggregate daily stats
       │
  ┌────▼────────────┐
  │ POST /report    │  ← Agent feedback
  │ refreshStats()  │     success_rate, latency → ranking improvement
  └─────────────────┘

Tech Stack

Component	Technology
Runtime	Cloudflare Workers
Framework	Hono
Database	Cloudflare D1 (SQLite)
Vector Search	CF Vectorize (1536-dim, cosine)
Text Search	FTS5 (OR + prefix, fallback path)
Embedding	OpenAI text-embedding-3-small
MCP Server	CF Agents SDK (McpAgent + Durable Objects)
Data Sources	Smithery, GitHub awesome-mcp, MCP Official Registry (~2000 services)
Cron	CF Cron Trigger (hourly)
Language	TypeScript

Project Structure

disvr/
├── wrangler.toml           # CF Workers config
├── schema.sql              # D1 database schema
├── src/
│   ├── index.ts            # Hono entry + REST routes
│   ├── discover.ts         # Core: semantic search + 4-dim ranking
│   ├── db.ts               # D1 CRUD + feedback stats
│   ├── crawl.ts            # Multi-source crawlers + embedAndIndex
│   ├── mcp.ts              # MCP Server (Streamable HTTP)
│   ├── types.ts            # TypeScript type definitions
│   ├── landing.ts          # Landing page HTML
│   └── pages/
│       ├── registry.ts     # Provider Registry page
│       ├── explorer.ts     # Agent Query Explorer page
│       └── analytics.ts    # Analytics Dashboard page
├── test/
│   ├── types.test.ts       # Type conversion tests
│   ├── discover.test.ts    # Matching engine tests
│   ├── db.test.ts          # D1 operations tests
│   ├── api.test.ts         # REST API integration tests
│   └── crawl.test.ts       # Crawler tests
└── .mcp.json               # MCP config example

Local Development

# Prerequisites: Node.js 22+
nvm use 22

# Install dependencies
npm install

# Local dev server
npx wrangler dev

# Run tests
npx vitest run

# Deploy
npx wrangler deploy

Environment Variables

# Set OpenAI API Key (for embeddings)
wrangler secret put OPENAI_API_KEY

Database Setup

# Create D1 database
wrangler d1 create disvr-db

# Run schema
wrangler d1 execute disvr-db --file=./schema.sql

# Create Vectorize index
wrangler vectorize create disvr-mcp-index --dimensions=1536 --metric=cosine

Design Philosophy

Spend Intelligence, Not Just Search

Disvr is not a directory. It's not a marketplace. It's a decision layer.

Traditional directories return a list and let you pick. Disvr returns a recommendation and tells you:

Why this tool is worth using
How its cost/quality ratio compares
What makes it better than alternatives

Closed-Loop Feedback is the Moat

Every time an agent reports a call result (success/failure, latency, cost), it feeds back into the ranking algorithm. More usage → smarter recommendations. This isn't a static database — it's a living intelligence system.

Dual-Path Search Guarantees Recall

Primary: OpenAI embedding → CF Vectorize vector search (semantic matching)
Fallback: FTS5 full-text search (OR + prefix wildcards)
Automatically degrades when embedding fails or vector search returns empty — always returns results

Roadmap

Core API (discover + report + health)
MCP Server (Streamable HTTP)
Smithery crawler (330+ services)
GitHub awesome-mcp crawler + Stars enrichment
MCP Official Registry crawler (1000+ services)
Landing page + 4 frontend pages
Custom domains (www.disvr.top + api.disvr.top)
npm SDK (@sylar_yan/disvr)
90 unit tests (types, discover, db, api, crawl)
Request logging + Analytics API
Daily stats cron aggregation
Health checks + multi-signal reputation scoring
User registration + API key management UI
Agent integration verification (MCP real-world testing)
Cost tracking dashboard
Payment protocol integration (Stripe MPP / x402)

Contributing

PRs and Issues are welcome!

🐛 Bug reports → GitHub Issues
💡 Feature requests → GitHub Issues
🔧 Code contributions → Fork & PR

Acknowledgments

Cloudflare Workers — Global edge compute
Hono — Lightweight web framework
Smithery — MCP service registry
OpenAI — text-embedding-3-small
CF Agents SDK — MCP Server implementation

License

MIT

disvr

Why Disvr?

✅ Before You Start

Quick Start

Option 1: MCP Server (Recommended)

Option 2: REST API

Live Demo

API Reference

`POST /discover` — Service Discovery

`POST /report` — Feedback Loop

`GET /health` — Health Check

MCP Tools

SDK

Architecture

Tech Stack

Project Structure

Local Development

Environment Variables

Database Setup

Design Philosophy

Spend Intelligence, Not Just Search

Closed-Loop Feedback is the Moat

Dual-Path Search Guarantees Recall

Roadmap

Contributing

Acknowledgments

License

Resources

Latest Blog Posts

MCP directory API

Why Disvr?

✅ Before You Start

Quick Start

Option 1: MCP Server (Recommended)

Option 2: REST API

Live Demo

API Reference

POST /discover — Service Discovery

POST /report — Feedback Loop

GET /health — Health Check

MCP Tools

SDK

Architecture

Tech Stack

Project Structure

Local Development

Environment Variables

Database Setup

Design Philosophy

Spend Intelligence, Not Just Search

Closed-Loop Feedback is the Moat

Dual-Path Search Guarantees Recall

Roadmap

Contributing

Acknowledgments

License

Resources

Latest Blog Posts

MCP directory API

`POST /discover` — Service Discovery

`POST /report` — Feedback Loop

`GET /health` — Health Check