Remove MCP server from project

- Delete mcp_server.py
- Remove MCP startup from __main__.py
- Remove process_mcp_transcribe_task from tasks.py
- Clean MCP references from README.md

README.md

@@ -7,7 +7,6 @@ ScrAIbe is a transcription and summarization service that:
 - Provides:
   - A web GUI for uploading audio and receiving transcripts via email.
   - A CLI and Python API for direct integration.
-  - An MCP-style HTTP API (OpenAPI) for LLMs and external systems.
   - A watch-folder mode for automatic transcription, summarization, and email delivery.
 
 No local speech models or heavy dependencies are required. ScrAIbe is designed as a thin client in front of your own AI services.
@@ -35,13 +34,6 @@ For more information: https://apstrom.ca
     - Final transcript (MD + DOCX + JSON) when ready.
     - Summary as MD + DOCX (if requested).
     - Error notification if processing fails.
-- MCP-style HTTP API (optional):
-  - Exposes an OpenAPI-compliant REST endpoint for external LLMs or services.
-  - Allows:
-    - Audio upload for transcription.
-    - Job status checks.
-    - Retrieval of transcript JSON (no summary).
-  - Enabled via MCP_SERVER_ENABLED=true.
 - Watch-folder mode (optional):
   - Monitors a directory for audio files.
   - For each file:
@@ -81,7 +73,6 @@ For more information: https://apstrom.ca
     - Output formatting (e.g., .md with transcript + summary)
   - Runs:
     - Web GUI (Gradio) – always enabled
-    - MCP-style HTTP API (FastAPI) – optional
     - Watch-folder mode – optional
     - Celery worker (async processing)
     - Redis (in-container by default)
@@ -233,19 +224,6 @@ Accent color (UI and emails):
     - Email headings, links, and email addresses
   - Default: #7C6DA0
 
-MCP-style HTTP API:
-
-- MCP_SERVER_ENABLED:
-  - Enable MCP-style HTTP API (default: false).
-  - Values: true/false.
-- MCP_SERVER_HOST:
-  - Bind address (default: 0.0.0.0).
-- MCP_SERVER_PORT:
-  - Port (default: 8000).
-- MCP_USE_CELERY:
-  - Use Celery for async transcription (default: true).
-  - If false, transcription runs in-process.
-
 Watch-folder mode:
 
 - WATCH_ENABLED:
@@ -355,8 +333,6 @@ Core runtime dependencies:
 - celery[redis]
 - redis
 - python-docx
-- fastapi
-- uvicorn
 - ffmpeg (for audio preprocessing)
 
 No local Whisper, PyTorch, or Pyannote models are required.