Fish Audio
This MCP server provides text-to-speech capabilities through Fish Audio's API, enabling AI assistants to generate high-quality speech from text with support for custom voice models and real-time streaming. Built by Daichi Okazaki using TypeScript with the official Fish Audio SDK, it offers two main tools: TTS generation with configurable voice references, audio formats (MP3, WAV, PCM, Opus), and streaming modes, plus voice reference listing for managing multiple voice models through ID, name, or tag selection. The implementation features both HTTP and WebSocket streaming for low-latency audio generation, automatic cross-platform audio playbook (macOS, Windows, Linux), real-time audio streaming with immediate playback, and flexible voice reference management supporting both single and multiple voice configurations, making it valuable for creating conversational AI applications, automated content narration, accessibility tools, and building AI assistants that need high-quality speech synthesis without manual Fish Audio dashboard interaction.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- media
- Source
- PulseMCP
- Repository
- github.com/da-okazaki/mcp-fish-audio-server
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Fish Audio from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.