Claude Watermark Remover
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| WATERMARK_MODEL | No | Any OpenRouter model id. Defaults to qwen/qwen3.7-plus (≈ $0.001 per 1,000 characters). A :free model gets low reasoning and busy retries by default, a paid one no reasoning. | qwen/qwen3.7-plus |
| OPENROUTER_API_KEY | Yes | Your OpenRouter API key from https://openrouter.ai/settings/keys. Stored by the MCP client (e.g. Claude Desktop or Claude Code), not by this program. Set a credit limit on the key. | |
| OPENROUTER_BASE_URL | No | Points the server at an API gateway instead of OpenRouter. There is no fallback to the real endpoint when the gateway fails. | |
| WATERMARK_PROVIDERS | No | Comma-separated OpenRouter provider slugs. The default pins qwen/qwen3.7-plus to alibaba. | |
| WATERMARK_REASONING | No | Reasoning setting: none, low, medium or high. Defaults depend on the model (free models get low reasoning, paid ones none). | |
| WATERMARK_TEMPERATURE | No | Sampling temperature for the rewrite. Default 0.7. | 0.7 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| remove_watermarkA | Remove a statistical AI watermark without humanizing: one rewrite by one model that is instructed to keep the meaning, structure, formatting and language of the text. Links, quotations, amounts and percentages are masked and return unchanged. Returns the rewritten text with novelty_percent (share of five-word sequences replaced; the target is 80%), layout_kept, model_calls and the cost OpenRouter reported. A rewrite that breaks the layout or leaves 70–140% of the source length is an error. No meaning check and no AI score are run: compare the result with the source. Texts of 750+ characters give a reliable share; shorter texts are processed but the share is coarse. |
| get_configurationA | Read which OpenRouter model, reasoning setting and temperature this server uses, and the measured presets available. Makes no model call. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools are trivially distinguishable: remove_watermark performs the rewrite (a model call), while get_configuration only reads server settings and explicitly makes no model call. There is no plausible scenario where an agent would confuse them.
Both names follow a clean snake_case verb_noun pattern (remove_watermark, get_configuration) with consistent imperative verbs. The convention is predictable and readable.
For a narrowly scoped watermark-removal server, one action plus one introspection tool is defensible, but two tools is on the thin side. There is no batch, retry, or verification operation, so the surface feels minimal.
The core lifecycle (configure -> rewrite) is present, but configuration is read-only with no setter, and the tool itself notes that no meaning check or AI-score is run, leaving verification entirely to the caller with no supporting tool. Minor but real gaps for an agent trying to validate or tune results.