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Glama
AceDataCloud

MCP Fish Server

by AceDataCloud
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
ACEDATACLOUD_API_TOKENYesYour AceDataCloud API token

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

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
fish_generate_audioB

Generate speech audio from text using Fish TTS.

Use this when:
- You want to convert text to speech
- You need AI-generated audio narration

Returns:
    JSON response containing task_id and audio data when complete.

Example:
    fish_generate_audio(
        text="Hello, welcome to our service!",
        reference_id="d7900c21663f485ab63ebdb7e5905036"
    )
fish_get_usage_guideA

Get a comprehensive guide for using the Fish TTS tools.

Provides detailed information on how to use the Fish tools effectively,
including parameters, examples, and best practices.

Returns:
    Complete usage guide for Fish TTS tools.
fish_list_modelsB

List available Fish voice models from the API.

Returns:
    JSON response from /fish/model.
fish_get_modelA

Get a Fish voice model by ID.

Returns:
    JSON response from /fish/model/{id}.
fish_get_taskA

Query the status and result of a Fish audio generation task.

Use this to check if a task is complete and retrieve the resulting audio URL.

Task states:
- 'pending': Task is queued — keep polling
- 'processing': Task is being processed — keep polling
- 'complete': Task finished successfully
- 'failed': Task failed (check error message)

Returns:
    Task status and result data including audio URL.
fish_get_tasks_batchA

Query the status of multiple Fish tasks at once.

Efficiently checks the status of multiple audio generation tasks in a
single request.

Returns:
    Status and result data for all queried tasks.

Prompts

Interactive templates invoked by user choice

NameDescription
fish_guideGuide for choosing the right Fish TTS tool.
fish_workflow_examplesCommon workflow examples for Fish TTS tasks.

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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

A3.8/5.0

Scored across 6 tools

Disambiguation5/5

Each tool has a clear, distinct role: generating audio, retrieving individual models, listing models, checking single or batch task status, and providing usage guidance. There is no meaningful overlap between any of the tools.

Naming Consistency5/5

All tools follow a consistent fish_ prefix with a clear verb_noun pattern: generate_audio, get_model, get_task, get_tasks_batch, get_usage_guide, list_models. The naming is predictable and easy to navigate.

Tool Count5/5

Six tools is an appropriate, well-scoped count for a TTS-focused server. Each tool serves a necessary function without redundancy or bloat.

Completeness4/5

The surface covers the core generation workflow: create a task, poll its status, check batches, and browse voice models. Minor gaps like canceling a task or listing all tasks without IDs are absent, but the main workflow is fully supported.

Maintenance

ActivityActive
ResponsivenessNo issues

Resources