← whysaid.ai

INDIVIDUAL MCP TOOL

check_provenance

Detect whether a piece of text was model-generated and whether this system has emitted something materially identical before.

whysaid.ainone authenticationAvailability not checked

LIVE ENDPOINT

https://api.whysaid.ai/mcp

No auth detected

Connect to this endpoint to inspect the live schema for check_provenance and invoke it with your own arguments.

Indexed input schema

{}

Risk classification

Inferred read-only · medium confidence · heuristic, not a guarantee.

  • No write-capable action terms were found; this is not proof that invocation has no side effects.

Parent server

whysaid.ai

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.whysaid]
url = "https://api.whysaid.ai/mcp"
enabled = true
Claude Code

.mcp.json

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

Settings → Connectors → Add custom connector

Name: whysaid
Remote MCP URL: https://api.whysaid.ai/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": {
    "whysaid": {
      "url": "https://api.whysaid.ai/mcp"
    }
  }
}
Visual Studio Code

.vscode/mcp.json

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

Client-specific MCP configuration

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

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

Related tools

  • verify_source — Confirm a URL is reachable and actually says what it is claimed to say, BEFORE you spend a long context reading or acting on it.
  • verify_claim — Independently verify a claim against a real check — an HTTP fetch, a file, or a command — instead of taking an assertion on trust.
  • answer_share — Ask a live AI assistant a buyer question and report whether a given brand is named, at what position, and which competitors appear instead.
  • verify_answer — Check an entire AI answer: open every source it cited, say which are real, which are missing or invented, and which are merely paywalled.
  • report_waste — Record work your agent run spent money on and then threw away, and get back your waste rate — wasted spend as a share of total spend.
  • waste_report — Read the agent-integrity ledger: total spend, spend that produced nothing usable, the waste rate, and a breakdown by failure kind and by agent.
  • pricing — What each Whysaid verification costs and how to pay.