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ryterpro-mcp

by apiihub33-cyber
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Ryter Pro MCP Server

An MCP server that exposes the Ryter Pro text humanizer API as a tool for MCP-compatible clients.

Tools

humanize_text

Humanize or rewrite text with the Ryter Pro API.

Inputs:

  • text: Text to humanize.

  • mode: Optional humanizer mode supported by your Ryter Pro API.

ryterpro_api_info

Return basic API configuration and documentation links.

Related MCP server: AI Humanizer MCP Server

Installation

Requires Python 3.10 or later.

pip install ryterpro-mcp

Configuration

Set your Ryter Pro API key before running the server:

export RYTERPRO_API_KEY="your_api_key_here"

Optional environment variables:

export RYTERPRO_BASE_URL="https://api.ryter.pro"
export RYTERPRO_TIMEOUT="60"

Run

ryterpro-mcp

The server uses the MCP stdio transport by default.

MCP Client Example

{
  "mcpServers": {
    "ryterpro": {
      "command": "ryterpro-mcp",
      "env": {
        "RYTERPRO_API_KEY": "your_api_key_here"
      }
    }
  }
}

For local development from this repository:

{
  "mcpServers": {
    "ryterpro": {
      "command": "python3",
      "args": ["-m", "ryterpro_mcp.server"],
      "env": {
        "RYTERPRO_API_KEY": "your_api_key_here"
      }
    }
  }
}

Links

License

MIT

Available Tools

2 tools
humanize_textD

Humanize text using the Ryter Pro API.

ParametersJSON Schema
NameRequiredDescriptionDefault
modeNo
textYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

D1.5/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It gives no information about side effects, authentication requirements, rate limits, or what happens to the input text. The phrase 'Humanize text' is completely opaque regarding API behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Although the description is a single sentence, it provides no substantive value beyond restating the tool name. This is under-specification rather than conciseness, as no information is front-loaded to aid the agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has two parameters, no schema descriptions, and no annotations, yet the description fails to address what humanization does, what 'mode' controls, or any usage conditions. Even with an output schema present, the description is grossly incomplete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, and the description does not explain the 'text' parameter beyond the tool name, while completely ignoring the optional 'mode' parameter. This leaves the agent without essential parameter semantics, especially for 'mode' which has no definition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Humanize text using the Ryter Pro API' essentially restates the tool name without explaining what 'humanize' means or what the transformation entails. It does not distinguish the tool from its sibling ryterpro_api_info, providing no unique functional context.

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?

There is no guidance on when to use this tool versus the sibling tool or any other alternatives. The description lacks any indication of typical use cases, prerequisites, or contexts where this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

ryterpro_api_infoA

Return Ryter Pro MCP server configuration and documentation links.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. The verb 'Return' suggests a read-only, non-mutating operation, and the tool appears to be a simple info endpoint. However, it does not disclose potential side effects, authentication requirements, or any limitations, leaving gaps for an agent to infer.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the action ('Return') and the object ('Ryter Pro MCP server configuration and documentation links'). Every word earns its place, with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity—no parameters and an output schema that presumably documents return values—the description is complete enough. It describes the tool's purpose sufficiently without needing to explain configuration details or documentation URLs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema confirms this with an empty properties object. The baseline for no parameters is 4, and the description does not need to add parameter-level detail since there are none.

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?

The description uses the specific verb 'Return' and identifies a clear resource: 'Ryter Pro MCP server configuration and documentation links.' It clearly distinguishes this tool from the sibling 'humanize_text' by stating a completely different function.

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?

There is no explicit guidance on when to use this tool versus alternatives, no mention of when not to use it, and no reference to sibling tools. Usage is only implied by the tool's name and generic description, which is insufficient for clear decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updatesv0.1.0
    • First observedhumanize_text
    • First observedryterpro_api_info
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.7/5.0

Scored across 2 tools

Disambiguation5/5

The two tools serve clearly distinct purposes: one performs text humanization, the other provides API configuration and documentation. There is no overlap or ambiguity.

Naming Consistency4/5

Mostly consistent with 'humanize_text' following a verb_noun pattern, while 'ryterpro_api_info' is more noun-oriented. The deviation is minor and both names are clear.

Tool Count3/5

With only 2 tools, the server feels thin for a text-processing API, but the scope is narrow enough that the count is acceptable.

Completeness4/5

The core functionality of humanizing text is covered, and the info tool provides necessary context. Minor gaps like batch processing or configuration options are not essential for the stated purpose.

Maintenance

ActivitySlowing
ResponsivenessNo issues

Resources

Related MCP Connectors

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