TTS Server

Server exposing three MCP tools over Streamable HTTP + legacy SSE, plus a matching REST API:

• voice_over — text-to-speech.
• visual_creator — turns a checklist of code/command entries into VS Code-style code screenshots and terminal-style command screenshots (PNG/SVG), for coding vlogs.
• video_renderer — stitches a project's synced voice_over narration + visual_creator screenshots into a single MP4, via ffmpeg.

Generated files (MP3s, images, MP4s) are written to a temp directory (safe for ephemeral disks on Render/Railway/Fly/etc.) and served back over HTTP so any LLM client or frontend can fetch them.

Project layout

The codebase is organized one directory per tool, so each tool's core logic, MCP schema, MCP handler, and tests live together — adding a fourth tool means adding one new directory under tools/, not touching four scattered files.

common/                        # shared across all tools
├── config.py                    # all env-var configuration in one place
├── files.py                       # filename generation, temp-path resolution, cleanup
├── logging.py                       # in-memory request log
├── formatting.py                      # file-size + timestamp helpers
└── project_store.py                     # manifest/order sync layer (shared by all 3 tools)

tools/                          # one self-contained directory per MCP tool
├── voice_over/
│   ├── core.py                    # generate_audio_core, TTSGenerationError (edge-tts wrapper)
│   ├── schema.py                    # MCP Tool() inputSchema definition
│   ├── handler.py                     # MCP call_tool logic for this tool
│   └── tests/
│       └── test_tts_core.py
│
├── visual_creator/
│   ├── core.py                    # generate_visuals_core, VisualCreatorError
│   ├── schema.py
│   ├── handler.py
│   ├── rasterize.py                 # SVG -> PNG rasterizer
│   ├── vlogshot/                      # vendored screenshot-rendering package (see below)
│   └── tests/
│       ├── test_visual_core.py
│       └── test_rasterize.py
│
└── video_renderer/
    ├── core.py                    # render_project_video, VideoRenderError (ffmpeg pipeline)
    ├── schema.py
    ├── handler.py
    └── tests/
        └── test_render_core.py

mcp_layer/                      # MCP protocol/transport only — no tool-specific logic
├── server.py                     # Server("voiceover-mcp-server") instance
├── registry.py                     # aggregates each tool's schema.py + handler.py
├── errors.py                         # shared {"success": false, "error": ...} helper
├── sse_asgi.py                         # legacy SSE transport
├── streamable_http_asgi.py               # Streamable HTTP transport
└── tests/
    ├── test_mcp_handlers.py
    └── test_mcp_transport.py

api/                             # REST layer only — imports from tools/*/core.py directly
├── app.py                         # FastAPI app factory: middleware, lifespan, routers
├── models.py                        # TTSRequest / TTSResponse Pydantic models
├── routes/                            # one file per resource
│   ├── root.py                          # GET / , GET /health
│   ├── tts.py                             # POST /api/v1/tts
│   ├── voices.py                            # GET /api/v1/voices
│   ├── audio.py                               # GET /api/v1/audio/{filename}
│   ├── visuals.py                               # GET /api/v1/visual/{filename}
│   ├── projects.py                                # GET /api/v1/project(s), .../video
│   └── logs.py                                      # GET /api/v1/logs
└── tests/
    ├── test_routes_misc.py
    ├── test_routes_tts.py
    └── test_routes_projects.py

tests/                           # cross-cutting tests only (shared fixtures, project_store)
├── test_files.py
├── test_formatting.py
└── test_project_store.py

conftest.py                      # project-root pytest fixtures (e.g. `client`), shared by every test dir above
run.py                           # entry point

tools/visual_creator/vlogshot/ is a vendored copy of the standalone vlog_screenshot_tool CLI project — same rendering code (checklist parsing, zip extraction, SVG rendering, themes, fonts), reused here as a library instead of being invoked as a subprocess.

See each tool's own README for details specific to that tool: tools/voice_over/README.md · tools/visual_creator/README.md · tools/video_renderer/README.md

Run it

pip install -r requirements.txt
cp .env.example .env   # edit as needed
python run.py

Server starts on http://0.0.0.0:8080 by default. Docs at /docs.

MCP tools

Connect an MCP client to /mcp (Streamable HTTP) or /mcp/sse (legacy SSE). All three tools below are exposed on the same server; each is documented in full in its own tools/{name}/README.md.

voice_over

• Input: text (required), voice, rate, pitch, volume, output_filename, and optionally project_id + order + label to group this clip with a matching visual_creator screenshot for later sync.
• Output: { "success": true, "content": "<original text>", "filename": "<name>.mp3", "timestamp": "..." }

The tool does not return audio bytes or a filesystem path — only the filename. Fetch the actual file with GET /api/v1/audio/{filename}.

visual_creator

• Input:
  • checklist (required) — array of entries, each one of:
    • a zip-lookup code entry: {file, start_line, end_line, label}
    • an inline code entry (no zip needed): {path, start_line, code, label}
    • a command entry (no zip needed): {type: "command", command, output, label}
  • zip_base64 — base64-encoded project zip; required only if checklist has at least one zip-lookup code entry
  • theme (dark / light / high-contrast, default dark)
  • style (vscode / minimal, default vscode)
  • font_size (default 22), width (default 1920), height (default 1080)
  • output_format (png / svg / both, default png)
  • optionally project_id (matched to voice_over calls by each checklist entry's own order)
• Output: { "success": true, "results": [{order, label, status, detail}, ...], "files": ["<name>.png", ...], "download_url_template": "/api/v1/visual/{filename}", "timestamp": "..." }

One bad entry never fails the whole call — results[i].status is OK, CLIPPED, or SKIPPED (reason) per entry. Fetch each generated file with GET /api/v1/visual/{filename}.

video_renderer

• Input: project_id (required — must have matching voice_over + visual_creator calls already made against it), transition (cut default / crossfade), crossfade_seconds (default 0.5).
• Output: { "success": true, "filename": "final_output.mp4", "total_duration_seconds": ..., "orders": [...], "warnings": [...], "download_url": "/api/v1/project/{project_id}/video", "timestamp": "..." }

Reads the project's manifest (written by voice_over/visual_creator), holds each order's screenshot(s) on screen for that order's narration duration, and concatenates every order into one MP4. Orders missing either audio or visual are skipped with a warning, not a hard failure. Fetch the result with GET /api/v1/project/{project_id}/video.

REST API (mirrors the MCP tools 1:1)

Method	Path	Purpose
GET	/	Service info
GET	/health	Health + temp dir status
GET/POST/DELETE	/mcp	MCP Streamable HTTP transport
GET	/mcp/sse	MCP legacy SSE transport
POST	/api/v1/tts	Generate speech, returns filename + download URL
GET	/api/v1/voices	List/filter available edge-tts voices
GET	/api/v1/audio/{filename}	Download/stream a generated clip
GET	/api/v1/visual/{filename}	Download a generated screenshot
GET	/api/v1/projects	List known project_ids
GET	/api/v1/project/{project_id}	Get a project's manifest
GET	/api/v1/project/{project_id}/{order}/{filename}	Download one order's audio/visual file
GET	/api/v1/project/{project_id}/video	Download the rendered MP4 (video_renderer output)
GET	/api/v1/logs	Recent request log (monitoring)

Storage model

• All audio, visuals, and rendered videos are written to a single ephemeral temp directory (TEMP_DIR, defaults to the OS temp dir + voiceover_mcp); visuals go in a visuals/ subfolder, project-synced files (including video_renderer's output) go under a projects/ subfolder.
• Filenames are sanitized and resolved with Path(...).name only — no path traversal via output_filename, checklist entries, or any download route.
• Each visual_creator call gets a short random filename prefix, so repeat calls (even with identical labels) never overwrite each other's output.
• AUDIO_TTL_SECONDS / VISUAL_TTL_SECONDS / project TTL (see common/config.py) control a startup cleanup sweep that deletes stale files.
• Because storage is ephemeral, files will not survive a server restart on most PaaS platforms — by design. Download endpoints return a clear 404 if a file has expired or the instance was recycled.

Testing

python -m pytest -v

pyproject.toml's testpaths covers tests/, tools/, mcp_layer/, and api/, so this one command discovers every test across the whole tree — each tool's own tests, the MCP dispatch tests, the REST route tests, and the shared/cross-cutting tests all run together. Currently 102 tests.

Covers: filename/path safety, TTS core logic (edge-tts mocked, no real network calls), visual_creator core rendering logic (inline code, command, and zip-lookup entries; bad-input errors), video_renderer's manifest-to-segments logic and ffmpeg pipeline (mocked subprocess calls plus real end-to-end renders when ffmpeg is available), all three MCP tool handlers, and all REST routes.

Environment variables

See .env.example. Key ones:

• PORT, HOST — server binding
• TEMP_DIR — override the shared audio/visuals/projects temp directory
• AUDIO_TTL_SECONDS, VISUAL_TTL_SECONDS — cleanup age thresholds
• DEFAULT_VOICE, DEFAULT_RATE, DEFAULT_PITCH, DEFAULT_VOLUME — TTS defaults
• FFMPEG_BINARY — override the ffmpeg binary video_renderer shells out to (defaults to the static binary bundled by imageio-ffmpeg, since this deploys on Render's Dockerfile-less native Python runtime)
• DEFAULT_TRANSITION, CROSSFADE_SECONDS, RENDER_TIMEOUT_SECONDS — video_renderer defaults