MCP 服务器

Moltline Humanizer

            com.moltlinestudio/humanizer
        

媒体与内容公开且可连接 MCP 2025-11-25

此 MCP 可以做什么

Analyzes writing for AI-generated style indicators, fingerprints writing voices, and supports humanization and rewrite verification.

ai_tell_scan

Ai Tell Scan

Scan a draft for the measurable tells of AI-generated prose. FREE. Flags stock phrases (with exact quotes), structural reflexes, uniform sentence rhythm, em-dash overuse, and hedging boilerplate — every flag cites the actual text. Typical input {"text": "<draft>"} returns {"reads_human_score": 0-100, "metrics": {"burstiness": ..., "avg_sentence_len": ..., ...}, "evidence": [{"type": "stock_phrase", "quote": "..."}], "note": "..."}. Use for a first read on whether a draft carries machine-writing signals. Reports measurable patterns, not a verdict on who wrote the text, and must not be used to accuse a person of anything. Not for rhythm detail (burstiness_report) or for a rewrite brief (humanize_plan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "empty text"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

只读幂等

输入模式

{'type': 'object', 'required': ['text'], 'properties': {'text': {'type': 'string', 'description': 'The draft to scan — at least one full sentence of plain text.'}}, 'additionalProperties': False}

输出模式

{'type': 'object', 'additionalProperties': True}

burstiness_report

Burstiness Report

Map a draft's sentence rhythm and find where it goes flat. FREE. Reports per-sentence lengths, the burstiness coefficient, and runs of similar-length sentences. Typical input {"text": "<draft>"} returns {"sentence_lengths": [12, 14, 13, 5, 28], "burstiness": 0.52, "flat_runs": [{"sentences": "1-3", "lengths": [12, 14, 13]}], "tip": "..."}. Use when prose reads flat and sentence-length pattern is the suspect. Not for a full inventory of tells (ai_tell_scan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "need 3+ sentences"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

只读幂等

输入模式

{'type': 'object', 'required': ['text'], 'properties': {'text': {'type': 'string', 'description': 'The draft to analyze; needs at least 3 sentences.'}}, 'additionalProperties': False}

输出模式

{'type': 'object', 'additionalProperties': True}

humanize_plan

Humanize Plan

Produce a precise rewrite brief that de-AIs a draft, with numeric targets. PREMIUM (license). Lists every flagged tell with its fix and sentence-rhythm surgery targets; when a voice_fingerprint result is supplied, adds numeric targets to hit that person's voice. Apply the brief with your agent, then confirm with verify_rewrite. Typical input {"text": "<draft>", "fingerprint": <voice_fingerprint result>} returns {"current_score": 0-100, "edit_list": ["..."], "numeric_targets": {...}, "process": ..., "integrity_note": ...}. Use after a scan has identified what to fix; returns a brief, not rewritten prose. Not for checking whether a rewrite worked (verify_rewrite). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

只读幂等

输入模式

{'type': 'object', 'required': ['text'], 'properties': {'text': {'type': 'string', 'description': 'The AI draft to plan a rewrite for.'}, 'fingerprint': {'type': 'object', 'default': None, 'description': 'Optional voice profile object exactly as returned by\nvoice_fingerprint; omit for a style-only pass.', 'additionalProperties': True}}, 'additionalProperties': False}

输出模式

{'type': 'object', 'additionalProperties': True}

verify_rewrite

Verify Rewrite

Verify a rewrite actually improved: score delta, meaning check, voice distance. PREMIUM (license). Compares reads-human score before/after, a meaning-preservation proxy, and (with a fingerprint) numeric distance to the target voice. Typical input {"original": "<draft>", "rewrite": "<edited draft>"} returns {"score_before": N, "score_after": N, "score_delta": N, "content_word_retention_pct": N, "remaining_tells": [...], "verdict": "Improved — ship it" | "Marginal — ..."}. Use only when both the before and the after text are available. Not for scoring a single draft (ai_tell_scan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "both texts must be non-empty"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

只读幂等

输入模式

{'type': 'object', 'required': ['original', 'rewrite'], 'properties': {'rewrite': {'type': 'string', 'description': 'The same content after the humanize_plan edits.'}, 'original': {'type': 'string', 'description': 'The draft before editing.'}, 'fingerprint': {'type': 'object', 'default': None, 'description': 'Optional voice profile object exactly as returned by\nvoice_fingerprint, to measure distance to the target voice.', 'additionalProperties': True}}, 'additionalProperties': False}

输出模式

{'type': 'object', 'additionalProperties': True}

voice_fingerprint

Voice Fingerprint

Build a measurable voice profile from samples of a person's real writing. FREE. Feed it 2+ samples (emails, posts, essays — 150+ words total) and use the result with humanize_plan / verify_rewrite. Typical input {"samples": ["<email text>", "<blog post>"]} returns {"label": "my-voice", "target_metrics": {"avg_sentence_len": ..., "burstiness": ..., ...}, "favorite_words": [...], "signature_habits": ["..."], "words_analyzed": N}. Use on samples the person actually wrote, to build a target profile. Not for scoring an unknown draft (ai_tell_scan) and not on text the person did not write. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "need 150+ words of real writing across the samples"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

只读幂等

输入模式

{'type': 'object', 'required': ['samples'], 'properties': {'label': {'type': 'string', 'default': 'my-voice', 'description': 'Optional name for this voice profile. Default "my-voice".'}, 'samples': {'type': 'array', 'items': {'type': 'string'}, 'description': 'List of real writing samples by the same person; 150+\nwords combined across all samples.'}}, 'additionalProperties': False}

输出模式

{'type': 'object', 'additionalProperties': True}

已添加

                            verify_rewrite
                        

2026年9月17日 12:36

已添加

                            humanize_plan
                        

2026年9月17日 12:36

已添加

                            burstiness_report
                        

2026年9月17日 12:36

已添加

                            voice_fingerprint
                        

2026年9月17日 12:36

已添加

                            ai_tell_scan
                        

2026年9月17日 12:36

服务器详情

版本

1.2.0

传输方式

Streamable HTTP

工具

延迟

1147 ms

端点

https://mcp.moltlinestudio.com/humanizer

近期扫描

成功

2026年10月1日 02:54

成功

2026年9月29日 03:02

成功

2026年9月27日 02:53

成功

2026年9月25日 03:02

成功

2026年9月23日 02:53

成功

2026年9月21日 03:00

成功

2026年9月19日 02:51

成功

2026年9月17日 13:00

成功

2026年9月17日 12:36

Moltline Humanizer

此 MCP 可以做什么

工具

近期工具变更

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