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fasuizu-br/brainiall-mcp-server

by Various

MCP Server for Brainiall Speech AI - pronunciation assessment, speech-to-text, and text-to-speech

F

MCP

fasuizu-br/brainiall-mcp-server

Added 1 June 2026

#brainiall #fastmcp #mcp #mcp-server #pronunciation #speech-ai #speech-to-text #stt

Overview

An MCP server that wraps Brainiall Speech AI to provide pronunciation assessment, speech-to-text, and text-to-speech capabilities. It exposes these speech functions through the Model Context Protocol for integration with compatible clients.

Best for

Best for
Developers who need to add Brainiall speech features to MCP-compatible applications

Use cases

  • Add pronunciation scoring to language learning apps
  • Enable speech-to-text transcription in MCP-based tools
  • Generate spoken audio from text via text-to-speech

Notes

An MCP server that wraps Brainiall Speech AI to provide pronunciation assessment, speech-to-text, and text-to-speech capabilities. It exposes these speech functions through the Model Context Protocol for integration with compatible clients.

0 stars on GitHub. Last updated 2026-03-11. Licensed MIT.

Use cases

  • Add pronunciation scoring to language learning apps
  • Enable speech-to-text transcription in MCP-based tools
  • Generate spoken audio from text via text-to-speech

Pros

  • Leverages the MCP protocol for standardized integration
  • Written in Python, easy to extend or modify
  • Open source with no licensing restrictions

Cons

  • Zero stars and no community adoption indicates limited testing
  • Requires a Brainiall API key and internet access
  • No documentation or usage examples provided in the repository

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Leverages the MCP protocol for standardized integration
  • Written in Python, easy to extend or modify
  • Open source with no licensing restrictions

Cons

  • Zero stars and no community adoption indicates limited testing
  • Requires a Brainiall API key and internet access
  • No documentation or usage examples provided in the repository