mirror of
https://github.com/jamiepine/voicebox.git
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feat(mcp): local MCP server exposes voicebox.* tools to AI agents
Mounts FastMCP at /mcp (Streamable HTTP) so Claude Code, Cursor, Windsurf, and the VS Code MCP extensions can call voicebox.speak, voicebox.transcribe, voicebox.list_captures, and voicebox.list_profiles against the running Voicebox server. Backend - new backend/mcp_server package (tools, middleware, profile resolve, pub/sub events); named mcp_server to avoid shadowing the installed mcp PyPI package FastMCP imports internally - app.py migrated from @app.on_event to lifespan= so FastMCP's session manager cohabits with Voicebox's startup/shutdown - new MCPClientBinding table + /mcp/bindings CRUD; ClientIdMiddleware reads X-Voicebox-Client-Id into a ContextVar and stamps last_seen_at - profile resolution precedence: explicit -> per-client binding -> capture_settings.default_playback_voice_id - POST /speak REST wrapper for non-MCP callers (shell, ACP, A2A) - GET /events/speak SSE broadcasts speak-start / speak-end so the pill surfaces agent-initiated speech - backend/mcp_shim proxy (plain httpx) for stdio-only MCP clients - PyInstaller spec updates + new --shim build target (~18 MB) Frontend - Settings -> MCP page with HTTP / stdio / claude-mcp-add copy snippets, default voice picker, per-client bindings table, connection status - useMCPBindings, useSpeakEvents hooks - CapturePill gains 'speaking' state; DictateWindow subscribes to SSE and emits dictate:show so the Rust side surfaces the pill window Native - tauri.conf.json externalBin now includes voicebox-mcp - show_dictate_window helper + dictate:show listener in main.rs - (also in this commit: InputMonitoringGate UX, hotkey_monitor tweaks, landing footer/navbar updates, new overview docs for captures / dictation / mcp-server / voice-personalities) Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>
This commit is contained in:
James Pine
co-authored by
Claude Opus 4.7
Claude Opus 4.7
parent
87c582ad54
commit
0cef2c9fe1
+100
-81
@@ -4,6 +4,7 @@ import asyncio
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import logging
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import os
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import sys
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from contextlib import asynccontextmanager
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from pathlib import Path
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@@ -68,15 +69,36 @@ def safe_content_disposition(disposition_type: str, filename: str) -> str:
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def create_app() -> FastAPI:
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"""Create and configure the FastAPI application."""
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from .mcp_server.server import build_mcp_server
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from .mcp_server.context import ClientIdMiddleware
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# Build the MCP app up-front so we can wire its lifespan into FastAPI's —
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# FastMCP's Streamable HTTP transport only works if its session manager
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# runs inside the parent ASGI lifespan.
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mcp = build_mcp_server()
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mcp_app = mcp.http_app(path="/", transport="http")
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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await _run_startup(app)
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async with mcp_app.router.lifespan_context(app):
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try:
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yield
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finally:
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await _run_shutdown()
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application = FastAPI(
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title="voicebox API",
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description="Production-quality Qwen3-TTS voice cloning API",
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version=__version__,
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lifespan=lifespan,
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)
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_configure_cors(application)
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application.add_middleware(ClientIdMiddleware)
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register_routers(application)
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_register_lifecycle(application)
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application.mount("/mcp", mcp_app)
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logger.info("MCP: mounted at /mcp")
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_mount_frontend(application)
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return application
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@@ -179,107 +201,104 @@ def _get_gpu_status() -> str:
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return "None (CPU only)"
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def _register_lifecycle(application: FastAPI) -> None:
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"""Attach startup and shutdown event handlers."""
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async def _run_startup(application: FastAPI) -> None:
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"""Database init, warnings, model-cache prep. Runs on lifespan entry."""
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import platform
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import sys
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@application.on_event("startup")
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async def startup_event():
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import platform
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import sys
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logger.info("Voicebox v%s starting up", __version__)
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logger.info(
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"Python %s on %s %s (%s)",
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sys.version.split()[0],
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platform.system(),
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platform.release(),
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platform.machine(),
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)
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logger.info("Voicebox v%s starting up", __version__)
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logger.info(
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"Python %s on %s %s (%s)",
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sys.version.split()[0],
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platform.system(),
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platform.release(),
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platform.machine(),
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)
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database.init_db()
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database.init_db()
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from .database.session import _db_path
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from .database.session import _db_path
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logger.info("Database: %s", _db_path)
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logger.info("Data directory: %s", config.get_data_dir())
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logger.info("Database: %s", _db_path)
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logger.info("Data directory: %s", config.get_data_dir())
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init_queue()
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init_queue()
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# Mark stale "generating" records as failed -- leftovers from a killed process
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from sqlalchemy import text as sa_text
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# Mark stale "generating" records as failed -- leftovers from a killed process
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from sqlalchemy import text as sa_text
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db = next(get_db())
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try:
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result = db.execute(
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sa_text(
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"UPDATE generations SET status = 'failed', "
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"error = 'Server was shut down during generation' "
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"WHERE status IN ('generating', 'loading_model')"
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)
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db = next(get_db())
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try:
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result = db.execute(
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sa_text(
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"UPDATE generations SET status = 'failed', "
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"error = 'Server was shut down during generation' "
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"WHERE status IN ('generating', 'loading_model')"
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)
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if result.rowcount > 0:
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logger.info("Marked %d stale generation(s) as failed", result.rowcount)
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)
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if result.rowcount > 0:
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logger.info("Marked %d stale generation(s) as failed", result.rowcount)
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from .database import VoiceProfile as DBVoiceProfile, Generation as DBGeneration
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from .database import VoiceProfile as DBVoiceProfile, Generation as DBGeneration
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profile_count = db.query(DBVoiceProfile).count()
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generation_count = db.query(DBGeneration).count()
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logger.info("Profiles: %d, Generations: %d", profile_count, generation_count)
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profile_count = db.query(DBVoiceProfile).count()
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generation_count = db.query(DBGeneration).count()
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logger.info("Profiles: %d, Generations: %d", profile_count, generation_count)
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db.commit()
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except Exception as e:
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db.rollback()
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logger.warning("Could not clean up stale generations: %s", e)
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finally:
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db.close()
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db.commit()
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except Exception as e:
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db.rollback()
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logger.warning("Could not clean up stale generations: %s", e)
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finally:
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db.close()
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backend_type = get_backend_type()
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logger.info("Backend: %s", backend_type.upper())
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logger.info("GPU: %s", _get_gpu_status())
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backend_type = get_backend_type()
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logger.info("Backend: %s", backend_type.upper())
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logger.info("GPU: %s", _get_gpu_status())
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# Warn if GPU architecture is not supported by this PyTorch build
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from .backends.base import check_cuda_compatibility
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from .backends.base import check_cuda_compatibility
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_compatible, _cuda_warning = check_cuda_compatibility()
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if not _compatible:
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logger.warning("GPU COMPATIBILITY: %s", _cuda_warning)
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_compatible, _cuda_warning = check_cuda_compatibility()
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if not _compatible:
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logger.warning("GPU COMPATIBILITY: %s", _cuda_warning)
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from .services.cuda import check_and_update_cuda_binary
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from .services.cuda import check_and_update_cuda_binary
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create_background_task(check_and_update_cuda_binary())
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create_background_task(check_and_update_cuda_binary())
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try:
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progress_manager = get_progress_manager()
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progress_manager._set_main_loop(asyncio.get_running_loop())
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except Exception as e:
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logger.warning("Could not initialize progress manager event loop: %s", e)
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try:
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progress_manager = get_progress_manager()
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progress_manager._set_main_loop(asyncio.get_running_loop())
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except Exception as e:
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logger.warning("Could not initialize progress manager event loop: %s", e)
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try:
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from huggingface_hub import constants as hf_constants
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try:
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from huggingface_hub import constants as hf_constants
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cache_dir = Path(hf_constants.HF_HUB_CACHE)
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cache_dir.mkdir(parents=True, exist_ok=True)
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logger.info("Model cache: %s", cache_dir)
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except Exception as e:
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logger.warning("Could not create HuggingFace cache directory: %s", e)
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cache_dir = Path(hf_constants.HF_HUB_CACHE)
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cache_dir.mkdir(parents=True, exist_ok=True)
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logger.info("Model cache: %s", cache_dir)
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except Exception as e:
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logger.warning("Could not create HuggingFace cache directory: %s", e)
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logger.info("Ready")
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logger.info("Ready")
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@application.on_event("shutdown")
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async def shutdown_event():
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logger.info("Voicebox server shutting down...")
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try:
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tts.unload_tts_model()
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except Exception:
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logger.exception("Failed to unload TTS model")
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try:
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transcribe.unload_whisper_model()
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except Exception:
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logger.exception("Failed to unload Whisper model")
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try:
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llm.unload_llm_model()
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except Exception:
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logger.exception("Failed to unload LLM model")
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async def _run_shutdown() -> None:
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"""Unload models on lifespan exit."""
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logger.info("Voicebox server shutting down...")
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try:
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tts.unload_tts_model()
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except Exception:
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logger.exception("Failed to unload TTS model")
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try:
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transcribe.unload_whisper_model()
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except Exception:
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logger.exception("Failed to unload Whisper model")
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try:
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llm.unload_llm_model()
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except Exception:
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logger.exception("Failed to unload LLM model")
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app = create_app()
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