A
licenseC
qualityD
maintenanceDetects AI-generated content and transforms robotic text into natural, human-like writing while improving grammar, readability, and preserving key terminology.
1
33 npm
4
MIT
humanizer
Server Details
Transform AI-generated text into natural, human-sounding content that bypasses AI detectors.
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- Status
- Unhealthy
- Uptime
- 0.0% over 64 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- GPTHuman-ai/mcp-server
- GitHub Stars
- 1
- Server Listing
- GPTHuman-Humanizer
TDQS
A3.6/5.0
Scored across 1 tool
Disambiguation5/5
There is only one tool, so there is no possibility of confusing it with another operation. Its purpose is clearly stated as transforming AI-generated text into a more human-sounding variant.
Naming Consistency5/5
The single tool uses a clear snake_case verb_noun pattern: humanize_text. Although there is no broader set to compare against, the convention is readable and predictable.
Tool Count3/5
A one-tool surface is thin by the rubric's standards, even though the server has a tightly focused purpose. The single tool is meaningful rather than trivial, but it leaves little room for alternative workflows.
Completeness4/5
The core operation is covered, including tone and rewrite mode, with clear input constraints. Minor gaps exist around handling long text or validating inputs before submission, but agents can work around these limitations.
Available Tools
1 toolhumanize_textHumanize TextBInspect
Transforms AI-generated text into a more natural, human-sounding variant while preserving the requested tone and rewrite mode. Input must be at least 300 characters and must not exceed 2,000 words.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | Optional rewrite mode. Defaults to `Balanced` when omitted. | |
| text | Yes | The text to humanize. Must be at least 250 characters and must not exceed 2500 words. | |
| tone | No | Optional tone for the rewritten text. Defaults to `College` when omitted. | |
| apiKey | No | The API key to use for the GPT Human API. Deprecated: Use the Authorization header Bearer instead. |
TDQS
B3.3/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=false and destructiveHint=false, so the mutation/external-service profile is covered. The description adds length constraints but says nothing about what the call returns, latency/cost, or that an API key/Authorization header is required for the external GPT Human API despite openWorldHint=true.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the purpose, no filler. The second sentence earns its place only in intent — its numbers are wrong, which is a correctness problem rather than a verbosity one.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a four-parameter text-transformation tool with no output schema, the description should clarify what the response looks like and how mode/tone choices differ, and it should explain the deprecated apiKey parameter versus the Authorization header. Instead it leaves those gaps and introduces a length-constraint conflict that an agent may resolve incorrectly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, which would normally set a baseline of 3, but the description actively contradicts the schema: it says 'at least 300 characters and must not exceed 2,000 words' while the schema specifies minLength 250 and a 2,500-word ceiling. Conflicting bounds on the required parameter are worse than no added information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('transforms AI-generated text into a more natural, human-sounding variant') plus the preserved attributes (tone, rewrite mode). With no sibling tools, nothing further is needed to distinguish it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this rather than re-prompting a model or editing manually, and no explanation of what 'Professional' vs 'Enhanced' or the four tone levels actually mean in practice. The only guidance is a length constraint.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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