ag-clarvia-aeo-check

# Clarvia AEO Check ## Overview Before adding any MCP server, API, or CLI tool to your agent workflow, use Clarvia to score its agent-readiness. Clarvia evaluates 15,400+ AI tools across four AEO dimensions: API accessibility, data structuring, agent compatibility, and trust signals. ## Prerequisites Add Clarvia MCP server to your config: ```json { "mcpServers": { "clarvia": { "command": "npx", "args": ["-y", "clarvia-mcp-server"] } } } ``` ## When to Use This Skill - Use when evaluating a new MCP server before adding it to your config - Use when comparing two tools for the same job - Use when building an agent that selects tools dynamically - Use when you want to find the highest-quality tool in a category ## How It Works ### Step 1: Score a specific tool Ask Claude to score any tool by URL or name: ``` Score https://github.com/example/my-mcp-server for agent-readiness ``` Clarvia returns a 0-100 AEO score with breakdown across four dimensions. ### Step 2: Search tools by category ``` Find the top-rated database MCP servers using Clarvia ``` Returns ranked results from 15,400+ indexed tools. ### Step 3: Compare tools head-to-head ``` Compare supabase-mcp vs firebase-mcp using Clarvia ``` Returns side-by-side score breakdown with a recommendation. ### Step 4: Check leaderboard ``` Show me the top 10 MCP servers for authentication using Clarvia ``` ## Examples ### Example 1: Evaluate before installing ``` Before I add this MCP server to my config, score it: https://github.com/example/new-tool Use the clarvia aeo_score tool and tell me if it's agent-ready. ``` ### Example 2: Find best tool in category ``` I need an MCP server for web scraping. Use Clarvia to find the top-rated options and compare the top 3. ``` ### Example 3: CI/CD quality gate Add to your CI pipeline using the GitHub Action: ```yaml - uses: clarvia-project/clarvia-action@v1 with: url: https://your-api.com fail-under: 70 ``` ## AEO Score Interpretation | Score | Rating | Meaning | |-------|--------|---------| | 90-100 | Agent Native | Built specifically for agent use | | 70-89 | Agent Friendly | Works well, minor gaps | | 50-69 | Agent Compatible | Works but needs improvement | | 30-49 | Agent Partial | Significant limitations | | 0-29 | Not Agent Ready | Avoid for agentic workflows | ## Best Practices - ✅ Score tools before adding them to long-running agent workflows - ✅ Use Clarvia's leaderboard to discover alternatives you haven't considered - ✅ Re-check scores periodically — tools improve over time - ❌ Don't skip scoring for "well-known" tools — even popular tools can score poorly - ❌ Don't use tools scoring below 50 in production agent pipelines without understanding the limitations ## Common Pitfalls - **Problem:** Clarvia returns "not found" for a tool **Solution:** Try scanning by URL directly with `aeo_score` — Clarvia will score it on-demand - **Problem:** Score seems low for a tool I trust **Solution:** Use `get_score_breakdown` to see which dimensions are weak and decide if they matter for your use case ## Related Skills - `@mcp-builder` - Build a new MCP server that scores well on AEO - `@agent-evaluation` - Broader agent quality evaluation framework ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.