Clarvia

Name: Clarvia
Author: clarvia-project

@clarvia-project

关于 Clarvia

AEO (Agent Engine Optimization) scanner — scores and benchmarks 12,800+ AI agent tools for discoverability, quality, and agent compatibility. 14 MCP tools for searching, scanning, comparing, and benchmarking.

#aeo #mcp #scanner #ai-agent #developer-tools #quality

基本信息

分类

其他

传输方式

stdio

发布者

clarvia-project

提交者

digitamaz

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "clarvia": {
      "command": "npx",
      "args": [
        "-y",
        "clarvia-mcp-server"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Clarvia?

Clarvia is an AEO (Agent Engine Optimization) scanner that scores AI agent tools (APIs, MCP servers) on how easily AI agents can discover, integrate, and trust them. It assigns a score from 0 to 100 across four dimensions: API Accessibility, Data Structuring, Agent Compatibility, and Trust Signals, plus an optional Onchain Bonus. It indexes over 15,400 services.

How to use Clarvia?

Install with one command: npx -y clarvia-mcp-server. Add to any MCP client configuration (Claude Desktop, Claude Code, Cursor, Windsurf, Cline, Continue.dev) or use the remote endpoint https://clarvia-api.onrender.com/mcp/. The Node.js MCP server provides 16 tools; a Python MCP server offers 24 tools.

Key features of Clarvia

AEO Score (0–100) for any AI tool, API, or MCP server.
Four scoring dimensions with detailed breakdowns.
Search over 15,400 indexed AI tools by keyword or score.
Safety gate tool (clarvia_gate_check) for agent workflows.
Batch checking and alternative finding tools.
Personalized upgrade recommendations for tool makers.

Use cases of Clarvia

Agents gating external tool calls to ensure reliability.
Tool makers auditing their own service and improving agent-readiness.
Discovering high-quality alternatives in a category.
CI/CD pipeline integration via GitHub Actions.
Comparing multiple tools side-by-side.

FAQ from Clarvia

What is an AEO Score?

An AEO Score (0–100) measures how well an AI tool is designed for autonomous agents, covering API accessibility, data structuring, agent compatibility, and trust signals.

How do I install the Clarvia MCP server?

Run npx -y clarvia-mcp-server or add the remote endpoint https://clarvia-api.onrender.com/mcp/ to any MCP client supporting Streamable HTTP transport.