Advanced TTS MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| synthesize_speechC | Convert text to speech with advanced voice controls and natural expression |
| batch_synthesizeC | Synthesize multiple text segments with optional merging and intelligent pacing |
| get_voicesB | Get list of available voices with their capabilities and supported features |
| get_statusC | Get processing status for a synthesis request |
| list_output_filesB | List saved audio files in the output directory with metadata |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| create_podcast_intro | Generate a professional podcast introduction with warm, engaging tone |
| create_tutorial_narration | Create clear, educational narration for tutorials and instructional content |
| create_marketing_copy | Generate persuasive marketing audio with confident, professional tone |
| create_accessibility_description | Generate clear audio descriptions for visual content accessibility |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Available TTS Voices | Comprehensive list of available voices and their capabilities |
| TTS Usage Examples | Examples demonstrating various TTS features and use cases |
TDQS
Scored across 5 tools
Each tool has a distinct, non-overlapping purpose: batch_synthesize handles multiple segments, synthesize_speech handles single conversions, get_status checks request status, get_voices lists voice options, and list_output_files manages saved files. The descriptions clearly differentiate their functions, eliminating ambiguity.
All tools follow a consistent verb_noun naming pattern (e.g., batch_synthesize, get_status, get_voices, list_output_files, synthesize_speech). The verbs (batch_, get_, list_, synthesize_) are appropriate and uniform, making the set predictable and easy to understand.
With 5 tools, the server is well-scoped for a TTS (text-to-speech) domain. The count is appropriate, covering core operations like synthesis, status checking, voice management, and file listing without being too sparse or bloated. Each tool earns its place in the workflow.
The tool set covers essential TTS operations: synthesis (single and batch), status tracking, voice discovery, and output management. A minor gap exists in lacking explicit tools for deleting or managing output files beyond listing, but agents can likely work around this, and core workflows are well-supported.