Giggy Speech MCP

io.github.GRQDigitalCapitalv1.0.0Updated Oct 8, 2026

Giggy speech tools for AI agents: discover voices and generate text-to-speech.

VerifiedStreamable HTTPWeb executableMedia & Design

Overview

AI-generated overview

Lets an assistant browse Giggy voices and submit text-to-speech generations, then poll for the finished audio URL.

What it does
A remote Streamable HTTP MCP server exposing Giggy speech tools: list_voices and list_my_voices for discovering available voice IDs, generate_speech for submitting a text-to-speech job, and get_speech_generation for checking job status. Generation is asynchronous: the tool returns durable metadata and a generation UUID rather than live audio bytes, and the finished audio is retrieved from the result URL once the status is completed. The endpoint is stateless and accepts POST requests.
When to use it
Use it when an assistant or coding agent should produce spoken audio from text through Giggy, for example narrating generated content or building voice output into an agent workflow. It suits clients that can poll a job until completion rather than expecting audio in the tool response.
Requirements
A remote MCP endpoint at over Streamable HTTP; no local package or runtime is needed. A Giggy API key is required and is sent as an Authorization bearer token, typically supplied through the GIGGY_API_KEY environment variable in the client configuration. Network access to giggy.ai is required.
Before you install
The Authorization bearer token is a secret API key; keep it out of prompts, source control, and browser JavaScript, and avoid committing configured client files. Speech generation is a paid Giggy service, so usage may incur charges. The server submits generation jobs and writes generation records on the account, and each new generation should use a fresh idempotency key to avoid duplicate work.

Installation

In SourceWeft

  1. Open Giggy Speech MCP in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "giggy-mcp": {
      "type": "http",
      "url": "https://giggy.ai/mcp"
    }
  }
}

README

Giggy MCP — text-to-speech for AI agents

[MCP Docs CI]

Giggy MCP is a remote Streamable HTTP Model Context Protocol (MCP) server for using Giggy text-to-speech from coding agents and AI clients.

It provides Giggy speech tools to Codex, Claude Code, Cursor, VS Code, Cline, Windsurf-compatible clients, and other MCP clients.

MCP registry and plugin directories

Giggy's remote speech MCP endpoint is:

https://giggy.ai/mcp

This repository contains the publication artifacts for:

See directory submission status and requirements.

A public registry listing, plugin submission, and approved plugin publication are separate steps. Consult the submission document for verified status.

Quick setup

Use Giggy MCP with Codex

Set GIGGY_API_KEY in your environment, then add to ~/.codex/config.toml:

toml
[mcp_servers.giggy-speech]url = "https://giggy.ai/mcp"bearer_token_env_var = "GIGGY_API_KEY"

Use Giggy MCP with Claude Code

Set GIGGY_API_KEY, then configure:

json
{  "mcpServers": {    "giggy-speech": {      "type": "http",      "url": "https://giggy.ai/mcp",      "headers": { "Authorization": "Bearer ${GIGGY_API_KEY}" }    }  }}

Keep API keys out of configuration files committed to source control.

Remote MCP server

text
https://giggy.ai/mcp

Transport:

text
Streamable HTTP

The current Giggy MCP endpoint is stateless and accepts POST requests.

Authentication

Use a Giggy API key:

text
Authorization: Bearer $GIGGY_API_KEY

Giggy API keys begin with:

text
giggy_sk_

Keep the key in your MCP client's secret or environment configuration.

Do not:

  • put it in ordinary prompts
  • commit it to source control
  • embed it in browser JavaScript

Speech tools

This repository documents these Giggy speech tools:

text
list_voiceslist_my_voicesgenerate_speechget_speech_generation

The MCP server may expose other Giggy tools outside the speech scope of this repository.

Recommended speech workflow

  1. Call list_voices or list_my_voices.
  2. Select the exact returned voice_id.
  3. Call generate_speech.
  4. Supply a fresh idempotency_key for each new intended generation.
  5. Save generation.generation_uuid.
  6. Call get_speech_generation while the status is queued or processing.
  7. When the status becomes completed, use generation.result.url.

Do not resubmit a new generation while polling an existing generation.

Use Giggy MCP with Codex

Set:

bash
export GIGGY_API_KEY="giggy_sk_..."

Then add this to:

text
~/.codex/config.toml
toml
[mcp_servers.giggy-speech]url = "https://giggy.ai/mcp"bearer_token_env_var = "GIGGY_API_KEY"

A ready-to-copy version is included at:

text
examples/codex-config.toml

Verify:

bash
codex mcp list

Use Giggy MCP with Claude Code

Set:

bash
export GIGGY_API_KEY="giggy_sk_..."

A project MCP configuration is included at:

text
examples/claude-code.mcp.json

Its contents are:

json
{  "mcpServers": {    "giggy-speech": {      "type": "http",      "url": "https://giggy.ai/mcp",      "headers": {        "Authorization": "Bearer ${GIGGY_API_KEY}"      }    }  }}

Copy that configuration to:

text
.mcp.json

in the project where Claude Code should use Giggy.

Then run:

bash
claude mcp list

or use:

text
/mcp

inside Claude Code.

Other MCP clients

Ready-to-copy client configurations are included for:

ClientExample
Codexexamples/codex-config.toml
Claude Codeexamples/claude-code.mcp.json
Cursorexamples/cursor.mcp.json
VS Codeexamples/vscode.mcp.json
Clineexamples/cline.mcp.json
Windsurf-compatible clientsexamples/windsurf.mcp.json

Cursor

Set:

bash
export GIGGY_API_KEY="giggy_sk_..."

Copy or merge:

text
examples/cursor.mcp.json

into:

text
.cursor/mcp.json

for project configuration, or:

text
~/.cursor/mcp.json

for global configuration.

VS Code

Copy or merge:

text
examples/vscode.mcp.json

into:

text
.vscode/mcp.json

VS Code will prompt securely for the Giggy API key.

Cline

Open Cline's MCP server configuration and copy the contents of:

text
examples/cline.mcp.json

Replace:

text
YOUR_GIGGY_API_KEY

in your local configuration only.

Do not commit the configured file.

Windsurf-compatible clients

For installations that use:

text
~/.codeium/windsurf/mcp_config.json

merge the contents of:

text
examples/windsurf.mcp.json

and replace:

text
YOUR_GIGGY_API_KEY

in the local configuration only.

Raw MCP examples

Set:

bash
export GIGGY_API_KEY="giggy_sk_..."

Initialize:

bash
./examples/initialize.sh

List tools:

bash
./examples/list-tools.sh

List public voices:

bash
./examples/list-voices.sh

Important behavior

generate_speech returns durable generation metadata.

It does not return live MP3 or PCM audio bytes through MCP.

For progressive PCM audio, use:

text
POST https://giggy.ai/v1/text-to-speech

with:

text
mode=streamingoutput_format=pcm_24000

Developer resources

Speech API documentation:

text
https://giggy.ai/docs/speech-api

OpenAPI:

text
https://giggy.ai/v1/openapi.json

Runnable examples:

text
https://github.com/GRQDigitalCapital/giggy-examples

Pricing:

text
https://giggy.ai/pricing

Official SDK and runnable examples:

Source: README.md at commit 5f84f4e

Tools

0
Tool metadata has not been indexed yet.

Version history

1
  1. v1.0.0LatestOct 8, 2026