AI or Not MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AI or Not MCP Server check if this image is AI-generated"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AI or Not MCP Server
An MCP (Model Context Protocol) server that integrates with the AI or Not API to detect AI-generated content in images, videos, audio, and text.
Features
Image Analysis: Detect AI-generated images, deepfakes, NSFW content, and image quality issues
Video Analysis: Detect AI-generated video, synthetic voices, AI music, and video deepfakes
Audio Analysis: Detect AI-generated music and synthetic voices
Text Analysis: Detect AI-written text with confidence scoring and annotations
API Health Check: Verify API availability
Related MCP server: ZeroTrue MCP Server
Prerequisites
Node.js 18+
An API key from AI or Not
Installation
From Source
git clone https://github.com/tymrtn/aiornot-mcp.git
cd aiornot-mcp
npm install
npm run buildFrom npm (coming soon)
npm install -g aiornot-mcpConfiguration
Environment Variables
Variable | Required | Default | Description |
| Yes | - | Your AI or Not API key |
| No |
| API base URL |
Claude Desktop / Claude Code
Add to your MCP settings file:
{
"mcpServers": {
"aiornot": {
"command": "node",
"args": ["/path/to/aiornot-mcp/build/index.js"],
"env": {
"AIORNOT_API_KEY": "your_api_key_here"
}
}
}
}Settings file locations:
Claude Desktop (macOS):
~/Library/Application Support/Claude/claude_desktop_config.jsonClaude Code:
~/.claude/mcp_servers.json
Usage
Running the Server
AIORNOT_API_KEY="your_api_key_here" node build/index.jsAvailable Tools
aiornot_analyze_media
Analyze media content for AI generation.
Parameters:
Parameter | Type | Required | Description |
| string | Yes | One of: |
| string | Conditional | Path to file (required for image/video/audio) |
| string | Conditional | Text content (required for text, min 250 chars) |
| string[] | No | Report types to include |
| string[] | No | Report types to exclude |
| string | No | Tracking identifier |
| boolean | No | Include block-level annotations (text only) |
| number | No | Override request timeout |
Report Types by Media:
Media Type | Available Reports |
Image |
|
Video |
|
aiornot_is_live
Check if the AI or Not API is available.
Examples
Analyze an image:
{
"media_type": "image",
"file_path": "/path/to/image.jpg"
}Analyze an image for specific checks:
{
"media_type": "image",
"file_path": "/path/to/image.jpg",
"only": ["ai_generated", "deepfake"]
}Analyze video including deepfake detection:
{
"media_type": "video",
"file_path": "/path/to/video.mp4",
"only": ["ai_video", "deepfake_video"]
}Analyze text:
{
"media_type": "text",
"text": "Your text content here (minimum 250 characters)...",
"include_annotations": true
}Analyze audio for synthetic voice:
{
"media_type": "audio_voice",
"file_path": "/path/to/audio.mp3"
}Response Format
The server returns structured JSON with:
media_type: The analyzed media typescores: Extracted confidence scores and verdictsresponse: Full API response
Example response for image analysis:
{
"media_type": "image",
"scores": {
"ai_generated": {
"verdict": "ai",
"ai_confidence": 0.95,
"human_confidence": 0.05
},
"deepfake": {
"is_detected": false,
"confidence": 0.02
}
},
"response": { ... }
}Timeouts
Default timeouts vary by media type:
Media Type | Default Timeout |
Image | 30 seconds |
Text | 30 seconds |
Video | 120 seconds |
Audio (music) | 120 seconds |
Audio (voice) | 120 seconds |
Use timeout_ms to override if needed.
Development
# Install dependencies
npm install
# Build
npm run build
# Watch mode
npm run watch
# Test with MCP Inspector
npm run inspectorLicense
MIT - see LICENSE
Links
AI or Not - API provider
Model Context Protocol - MCP specification
MCP SDK - TypeScript SDK
Available Tools
2 toolsaiornot_analyze_mediaB
Analyze image, video, audio (music/voice), or text using the AI or Not API and return confidence scores.
Inputs: media_type (required), only, text, excluding, +4 more.
aiornot_is_liveA
Check if the AI or Not API is live.
Inputs: no named parameters.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 2 tools
The two tools are completely distinct: one performs media analysis and the other checks API liveness. There is no possible confusion between them.
Both tools share the consistent `aiornot_` prefix and use snake_case, but `analyze_media` is a clear verb_noun while `is_live` is a status-style name rather than an action on an object. Minor deviation in an otherwise predictable pattern.
With only two tools, the server is minimal, but the narrow purpose of wrapping the AI or Not API makes the count reasonable. It is slightly thin but not insufficient.
The analysis tool covers all supported media types (image, video, audio, text) and returns confidence scores, while the liveness tool covers API availability. For the stated purpose, there are no obvious gaps.
Maintenance
Related MCP Connectors
Free read-only checks for evidence of AI use in text, links, images, saved prompts and C2PA.
Check whether a video was generated by AI (Sora, Veo, Kling, HeyGen and others).
Detect AI-generated images, videos, and audio with identifAI's deepfake detection tools.
YouTube and video analysis, C2PA marking for AI images, lossless EXIF/GPS removal. Pay per call.
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