disvr

disvr

Tool search engine for AI agents. One API call to discover the best MCP server for any task. 900+ services indexed with 4-dimensional value ranking.

Category
访问服务器

README

<h1 align="center">🔍 Disvr</h1>

<p align="center"> <strong>Spend Intelligence for AI Agents — the "Yelp for the Agent Economy"</strong> </p>

<p align="center"> <a href="https://www.disvr.top"><img src="https://img.shields.io/badge/Live-www.disvr.top-00d4aa?style=for-the-badge" alt="Live Site"></a> <a href="https://api.disvr.top/health"><img src="https://img.shields.io/badge/API-Online-62fae3?style=for-the-badge" alt="API Status"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/License-MIT-blue.svg?style=for-the-badge" alt="MIT License"></a> </p>

<p align="center"> <a href="#why-disvr">Why Disvr</a> · <a href="#quick-start">Quick Start</a> · <a href="#api-reference">API</a> · <a href="#architecture">Architecture</a> · <a href="https://www.disvr.top/explorer">Live Demo</a> · <a href="docs/README_zh.md">中文文档</a> </p>


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

  • [x] Core API (discover + report + health)
  • [x] MCP Server (Streamable HTTP)
  • [x] Smithery crawler (330+ services)
  • [x] GitHub awesome-mcp crawler + Stars enrichment
  • [x] MCP Official Registry crawler (1000+ services)
  • [x] Landing page + 4 frontend pages
  • [x] Custom domains (www.disvr.top + api.disvr.top)
  • [x] npm SDK (@sylar_yan/disvr)
  • [x] 90 unit tests (types, discover, db, api, crawl)
  • [x] Request logging + Analytics API
  • [x] Daily stats cron aggregation
  • [x] Health checks + multi-signal reputation scoring
  • [x] 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!


Acknowledgments


License

MIT


<p align="center"> <strong>Stop guessing. Start discovering.</strong> <br/> <a href="https://www.disvr.top">www.disvr.top</a> · <a href="https://api.disvr.top/mcp">MCP Server</a> · <a href="https://api.disvr.top/health">API Status</a> </p>

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选