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Get Started Free →Score any MCP server, API, or CLI for agent-readiness using Clarvia AEO (Agent Experience Optimization). Search 15,400+ indexed tools before adding them to your workflow.
.claude/skills/clarvia-aeo-check/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | — | — |
| case-11 | ✗→✓ | ▲ Improved | — | — |
| case-07 | ✗→✓ | ▲ Improved | — | — |
| case-20 | ✗→✓ | ▲ Improved | — | — |
| case-12 | ✗→✓ | ▲ Improved | — | — |
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.
Add Clarvia MCP server to your config:
json{ "mcpServers": { "clarvia": { "command": "npx", "args": ["-y", "clarvia-mcp-server"] } } }
Ask Claude to score any tool by URL or name:
Score https://github.com/example/my-mcp-server for agent-readinessClarvia returns a 0-100 AEO score with breakdown across four dimensions.
Find the top-rated database MCP servers using ClarviaReturns ranked results from 15,400+ indexed tools.
Compare supabase-mcp vs firebase-mcp using ClarviaReturns side-by-side score breakdown with a recommendation.
Show me the top 10 MCP servers for authentication using ClarviaBefore 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.I need an MCP server for web scraping. Use Clarvia to find the
top-rated options and compare the top 3.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
| 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 |
Solution: Try scanning by URL directly with aeo_score — Clarvia will score it on-demand
Solution: Use get_score_breakdown to see which dimensions are weak and decide if they matter for your use case
@mcp-builder - Build a new MCP server that scores well on AEO@agent-evaluation - Broader agent quality evaluation framework| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-03 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-11 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-07 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-23 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-05 | pass→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-20 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-12 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-19 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-22 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-21 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-18 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-06 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-08 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-01 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-02 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-16 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-14 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-04 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-09 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-10 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-13 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-15 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-17 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +70 percentage points is the difference between those two pass rates over the 23 comparable cases.
The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.
Other measured skills in the registry, with their headline benchmark lift.