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AITuber MCP Server

AITuber MCP Server

Official
by aituberapp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

execute_api

Execute authenticated API requests to the AITuber platform. Use search_api to discover endpoints and parameters before calling this tool.

Instructions

Execute a request against the AITuber API. Use search_api first to find the right endpoint and parameters. Handles authentication automatically.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "method": "<method>",
      "path": "<path>"
    },
    "name": "execute_api"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyNoRequest body (for POST/PUT), e.g. { "script": "...", "mediaType": "images" }
pathYesAPI endpoint path, e.g. /videos, /videos/generate, /voices, /subscription
queryNoQuery parameters as key-value pairs, e.g. { "limit": "10", "gender": "female" }
methodYesHTTP method
pathParamsNoPath parameter substitutions, e.g. { "id": "abc-123" } for /videos/{id}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.12.0

TDQS

A4/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It mentions automatic authentication but does not disclose potential destructive behavior (e.g., creating/modifying resources) or rate limits. Minimal behavioral context beyond the basic operation.

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?

Two concise sentences, front-loaded with the core purpose, followed by usage guidance and a notable behavior (auth handling). No wasted words.

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

Completeness2/5

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

Lacks return value information (no output schema and no description of what the response looks like). Given 5 parameters with nested objects, a usage example would improve completeness. Does not explain how parameter interactions work (e.g., when to use query vs pathParams).

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description adds no additional parameter meaning beyond the schema's own descriptions. The only extra info is about authentication, which is not parameter-specific.

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?

Explicitly states it executes requests against the AITuber API, with a clear verb (execute) and resource (AITuber API). It also distinguishes from sibling search_api by advising to use search_api first.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance: use search_api first to find endpoint and parameters. Also mentions automatic authentication handling, helping the agent understand prerequisites and workflow.

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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