Integration

Detecting AI integration

Detecting AI (detecting-ai.com) checks and rewrites text. An agent can score how likely a text was written by AI (document percentage plus sentence-level AI or Human labels), rewrite a text with a humanizer model, and check a text for plagiarism against web sources with the matching sentences and links. Every call bills the input word count against the feature's own monthly word balance (a paid API plan is required), and results are review signals, not proof of authorship. Texts are limited to 160,000 characters. The MCP server and the website's account, history and payment routes are not exposed. Authentication is an API key from the Detecting AI dashboard, sent in the X-API-Key header.

Connect Detecting AI How integrations work

Ask it in chat

Say what should happen.
The workflow builds itself.

When this happens, do that in Detecting AI.Built from the 3 Detecting AI tools below, on the connection you add once.

What you can do with Detecting AI

Each of these is one operation on one endpoint, available both as a workflow step and as a tool an AI agent can call on its own. Nothing bundles several operations into one action, so what a run did stays readable afterwards.

Most endpoints run on the free plan. A few, mainly the ones that publish on your behalf, need a paid plan.

Ai detection, 1 operation

detect_ai_textDetect ai textPOSTScores how likely a text was written by AI. With version v3 the answer gives ai_percentage and sentence-level AI or Human labels with 0 to 1 scores. Bills the input word count against the detector balance.

Humanized text, 1 operation

humanize_textHumanize textPOSTRewrites a text with a humanizer model and returns the editable rewrite; review it for meaning, facts, names and links. Bills the input word count against the humanizer balance.

Plagiarism check, 1 operation

check_plagiarismCheck plagiarismPOSTSearches the web for sentence-level overlap with a text and returns each matching sentence with its source link and similarity, plus plagiarism_score. Bills the input word count against the plagiarism balance.

Use Detecting AI from Claude Code, Cursor or Codex

Connect Detecting AI in LiveContext, create an API key in Settings, then add the LiveContext MCP server to your client. Its Detecting AI operations become tools the client can call, next to every other integration you connected.

Claude Code

claude mcp add --transport http livecontext https://livecontext.ai/mcp --header "X-API-Key: YOUR_API_KEY"

Codex (~/.codex/config.toml)

[mcp_servers.livecontext]
url = "https://livecontext.ai/mcp"

[mcp_servers.livecontext.http_headers]
"X-API-Key" = "YOUR_API_KEY"

Cursor, Claude Desktop and other JSON configs

{
  "mcpServers": {
    "livecontext": {
      "type": "http",
      "url": "https://livecontext.ai/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}

Set up the MCP server step by step

How to connect Detecting AI

Create your workspace
Sign up free. Nothing to install.
Connect Detecting AI once
Add your Detecting AI connection in Settings. Every tool from this integration reuses it, and secrets are encrypted at rest and visible only to you.
Describe the job in chat
The workflow builds itself in front of you and picks the endpoints it needs. Drag the steps yourself on the canvas whenever you would rather be explicit.