Skip to main content
Glama
callremind

CallRemind MCP Server

Official
by callremind

generateTts

Convert text into spoken audio with a single API request, choosing from multiple TTS providers and formats to get a playable audio file URL for immediate use.

Instructions

Synthesize TTS audio directly (POST /v1/tts/generate). Provider: openai | elevenlabs | minimax | qwen_flash | qwen_plus | kokoro | edge. Returns a playable audio file URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to synthesize
styleNoSpeaking style, e.g. neutral
voiceNoVoice id for the selected provider
formatNomp3 (default), pcm, wav, opus, aac, flac
agent_idNoIf set, the generated audio is saved as the agent's notification clip
providerNoTTS provider (default openai)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.6

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden and does disclose the POST endpoint, direct synthesis behavior, and a playable audio file URL. However, it omits auth requirements, default provider, rate/cost considerations, and the fact that return_format can be base64 instead of a URL.

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

Conciseness4/5

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

The description is compact and front-loaded: endpoint, providers, and output are all present with no significant fluff. The word 'directly' adds marginal value and the provider list is a bit telegraphic, but nothing is wasted.

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

Completeness3/5

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

Core information needed to call the tool (endpoint, providers, output) is present, and the schema explains parameters well. Missing context includes how this relates to the many sibling TTS preview/list/call tools and the default return variant; for a parameter-rich tool with no output schema, it is adequate but not rich.

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?

The input schema already provides full descriptions for every parameter and an enum for provider, so the description's repeated provider list and URL note add little semantic value beyond the schema. Baseline 3 is appropriate because schema description coverage is 100%.

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

Purpose4/5

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

States a specific verb ('synthesize') and resource ('TTS audio') plus the endpoint and the output type. It is clearly distinct from call-making and preview siblings by saying 'directly' and mentioning a playable audio URL, though it does not explicitly name an alternative sibling.

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?

No explicit guidance about when to choose this tool over the many related TTS/call tools. It weakly implies direct generation rather than preview or calling, but it never states alternatives, exclusions, or selection conditions.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/callremind/callremind-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server