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AI & Machine Learning

ora.ai

Evaluates domains for AI agent readiness and provides a leaderboard and search for agent-friendly APIs.

2 endpoints26 known toolsFirst detected July 18, 2026Last detected August 26, 2026

ENDPOINT 1

https://ora.ai/api/mcp

No auth detected

MCP server metadata

Name
ora
Version
1.21.0
Capabilities
tools.listChangedresources.listChanged
Server instructions

Use ora to discover agent-ready products, check agent-readiness scores, and submit or read agent feedback. Start with get_score or discover_products for read-only lookups. Use search_capabilities to find pay-per-call API endpoints payable with x402/MPP stablecoin payments (no API key). Use scan_domain to run a fresh audit. After shipping a fix, call run_checks with check ids from list_checks to re-verify just the affected checks instead of running a full scan. To submit feedback about a product or a specific check result, first call get_verification_challenge to prove you are an agent, then call submit_feedback or submit_check_feedback with the verified token. Ora also publishes skills for coding agents (e.g. agent-ready-website): call list_skills to see them, then get_skill to fetch one and follow it; the same artifacts are readable as skill:// resources, with a skill://index.json catalog.

Known tools 13

scan_domain

Scan a domain for agent-readiness.

Inferred read-only
get_score

Get the cached agent-readiness score for a domain.

Inferred read-only
get_leaderboard

Get the ora leaderboard - ranked list of domains by agent-readiness score.

Inferred read-only
discover_products

Find the most agent-ready products for a given need.

Inferred read-only
search_capabilities

Search pay-per-call API capabilities agents can invoke with x402/MPP stablecoin payments - no API key or signup.

Potential side effects
get_verification_challenge

Get a verification challenge to prove you are an AI agent before submitting feedback.

Inferred read-only
submit_feedback

Submit agent feedback for a product.

Inferred read-only
submit_check_feedback

Report an issue with a specific check result for a domain.

Inferred read-only
get_feedback

Get agent feedback for a product.

Inferred read-only
list_skills

List the skills Ora publishes for coding agents.

Inferred read-only
get_skill

Fetch an Ora skill by name (see list_skills) and follow it step by step to complete the task.

Inferred read-only
list_checks

List the full catalog of checks behind ora's agent-readiness score: every check id with its layer, max score, applicability, tier, and maturity.

Inferred read-only
run_checks

Run a selected subset of checks against a URL and get per-check results back - the re-verify step after shipping a fix, with check ids from list_checks.

Inferred read-only

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.ora]
url = "https://ora.ai/api/mcp"
enabled = true
Claude Code

.mcp.json

{
  "mcpServers": {
    "ora": {
      "type": "http",
      "url": "https://ora.ai/api/mcp"
    }
  }
}
Claude Desktop

Settings → Connectors → Add custom connector

Name: ora
Remote MCP URL: https://ora.ai/api/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "ora": {
      "url": "https://ora.ai/api/mcp"
    }
  }
}
Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code 
{
  "servers": {
    "ora": {
      "type": "http",
      "url": "https://ora.ai/api/mcp"
    }
  }
}
Generic MCP

Client-specific MCP configuration

{
  "name": "ora",
  "transport": "streamable-http",
  "url": "https://ora.ai/api/mcp"
}
MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

ENDPOINT 2

https://ora.ai/skill/mcp

No auth detected

MCP server metadata

Name
ora
Version
1.21.0
Capabilities
tools.listChangedresources.listChanged
Server instructions

Use ora to discover agent-ready products, check agent-readiness scores, and submit or read agent feedback. Start with get_score or discover_products for read-only lookups. Use search_capabilities to find pay-per-call API endpoints payable with x402/MPP stablecoin payments (no API key). Use scan_domain to run a fresh audit. After shipping a fix, call run_checks with check ids from list_checks to re-verify just the affected checks instead of running a full scan. To submit feedback about a product or a specific check result, first call get_verification_challenge to prove you are an agent, then call submit_feedback or submit_check_feedback with the verified token. Ora also publishes skills for coding agents (e.g. agent-ready-website): call list_skills to see them, then get_skill to fetch one and follow it; the same artifacts are readable as skill:// resources, with a skill://index.json catalog.

Known tools 13

scan_domain

Scan a domain for agent-readiness.

Inferred read-only
get_score

Get the cached agent-readiness score for a domain.

Inferred read-only
get_leaderboard

Get the ora leaderboard - ranked list of domains by agent-readiness score.

Inferred read-only
discover_products

Find the most agent-ready products for a given need.

Inferred read-only
search_capabilities

Search pay-per-call API capabilities agents can invoke with x402/MPP stablecoin payments - no API key or signup.

Potential side effects
get_verification_challenge

Get a verification challenge to prove you are an AI agent before submitting feedback.

Inferred read-only
submit_feedback

Submit agent feedback for a product.

Inferred read-only
submit_check_feedback

Report an issue with a specific check result for a domain.

Inferred read-only
get_feedback

Get agent feedback for a product.

Inferred read-only
list_skills

List the skills Ora publishes for coding agents.

Inferred read-only
get_skill

Fetch an Ora skill by name (see list_skills) and follow it step by step to complete the task.

Inferred read-only
list_checks

List the full catalog of checks behind ora's agent-readiness score: every check id with its layer, max score, applicability, tier, and maturity.

Inferred read-only
run_checks

Run a selected subset of checks against a URL and get per-check results back - the re-verify step after shipping a fix, with check ids from list_checks.

Inferred read-only

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.ora]
url = "https://ora.ai/skill/mcp"
enabled = true
Claude Code

.mcp.json

{
  "mcpServers": {
    "ora": {
      "type": "http",
      "url": "https://ora.ai/skill/mcp"
    }
  }
}
Claude Desktop

Settings → Connectors → Add custom connector

Name: ora
Remote MCP URL: https://ora.ai/skill/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "ora": {
      "url": "https://ora.ai/skill/mcp"
    }
  }
}
Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code 
{
  "servers": {
    "ora": {
      "type": "http",
      "url": "https://ora.ai/skill/mcp"
    }
  }
}
Generic MCP

Client-specific MCP configuration

{
  "name": "ora",
  "transport": "streamable-http",
  "url": "https://ora.ai/skill/mcp"
}
MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

TRUST AND VERIFICATION EVIDENCE

Trust Data Available

BuiltWith Trust API v2 evidence for ora.ai was fetched 2026-08-03T17:16:16.099Z and is being refreshed.

Trust status Trusted

ora.ai is assessed as Trusted: Domain has an established technology history spanning over a year.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.