Slop or Not

What tools does the Slop or Not MCP server provide?

The server provides six tools for the checks agents usually need: status, text detection, readability, cleanup, image detection, and raw image scoring.

Every result below is real output, captured from Slop or Not 1.1.1 for Mac in August 2026 and abridged where marked.

Confirms the app is installed, the binary can run, and Pro is active before the agent starts a workflow.

{ "pro": true, "version": "1.1.1" }

Scores a passage with the on-device AI text detection model and returns a verdict, score, language, sentence count, and readability metrics.

{ "text": "<text>", "include_readability": true, "language_code": "en", "locale": "en-US" }

{ "kind": "result", "verdict": "most_likely_real", "score": 0.1259, "language": "en", "sentence_count": 2, "generator": null, "input_truncated": false, "readability": { "language": "en", "language_confidence": 0.9998, "scores": [ { "kind": "fleschReadingEase", "value": 50.85, "label": "Fairly difficult", … }, { "kind": "fleschKincaidGradeLevel", "value": 16.97, … } ], "word_count": 87, "sentence_count": 2, "avg_words_per_sentence": 43.5, "warnings": [ … ], "full": { "consensus": { … }, "genre": { … }, "grade_label": { … }, … } } }

Computes reading-level metrics without running AI detection.

{ "text": "<text>", "language_code": "en", "locale": "en-US" }

{ "language": "en", "language_confidence": 0.9998, "scores": [ { "kind": "fleschReadingEase", "value": 50.85, "label": "Fairly difficult", … }, { "kind": "fleschKincaidGradeLevel", "value": 16.97, … } ], "avg_words_per_sentence": 43.5, "sentence_count": 2, "word_count": 87, "warnings": [ … ], "full": { "consensus": { … }, "genre": { … }, "grade_label": { … }, … } }

Strips zero-width characters, homoglyphs, and fancy punctuation before the next detection pass.

{ "text": "<text>", "language_code": "en", "remove_invisibles": true, "remove_punctuation": true, "remove_homoglyphs": true, "britishize": false }

{ "cleaned_text": "He said \"hello\" - and left.", "language": "en", "removed_invisibles": 1, "punctuation_replacements": 3, "homoglyphs_replaced": 0, "british_substitutions": 0 }

Checks JPEG, PNG, HEIC, or WebP image bytes locally with C2PA and IPTC provenance reads and an on-device model fallback. The result names its detection_source, so an agent can tell a provenance hit from a model score.

{ "image_base64": "<base64>", "recognize_text": false }

{ "kind": "result", "verdict": "probably_ai_slop", "score": 0.6429, "generator": null, "detection_source": "ml", "watermark_provider": null, "watermark_confidence": null, "recognized_text": null, "recognized_sentence_count": null }

Returns the raw OmniAID image score when an agent needs the model signal without the full image-detection response. Needs the OmniAID model installed in the app.

{ "image_base64": "<base64>" }

{ "raw_slop_score": 0.33984375 }

After restart, ask your agent to run slop_status. The expected result is a tool call that reports the local app and Pro state without an error. A call that needs Pro comes back as a tool error (isError: true) while the server keeps running, so one blocked call never ends the session.

{ "pro": true, "version": "1.1.1" }

Only register MCP servers you trust. The Slop or Not MCP server is bundled with the signed Mac app, and the snippets on this page point at that exact app-bundle binary.