Speechmatics MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Speechmatics MCP Server Transcribe ~/meetings/team-sync.mp4 with speaker diarization"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Speechmatics MCP Server for Claude Code

An MCP (Model Context Protocol) server that gives Claude Code the ability to transcribe audio and video files using the Speechmatics Batch API.
What This Does
Once installed, Claude Code gains access to transcription tools that allow you to:
Transcribe single files - Convert any audio/video file to text
Batch transcribe directories - Process entire folders of media files in parallel
Speaker diarization - Identify different speakers (S1, S2, etc.) in conversations
Search transcripts - Use Claude's native Grep tool to search across all your transcripts
Example usage in Claude Code:
"Transcribe the meeting recording at ~/Downloads/meeting.mp4"
"Transcribe all the podcasts in ~/Podcasts with speaker identification"
"Search my transcripts for mentions of 'quarterly budget'"Related MCP server: mocoVoice MCP Server
Requirements
Python 3.11+
ffmpeg (for audio duration detection)
Speechmatics API key (free tier available)
Installation
1. Install ffmpeg
# macOS
brew install ffmpeg
# Ubuntu/Debian
sudo apt install ffmpeg
# Windows
winget install ffmpeg2. Clone and install dependencies
git clone https://github.com/ArchieMcM234/speechmatics_claude_code_mcp.git
cd speechmatics_claude_code_mcp
uv sync3. Register the MCP server
Add to your Claude Code config file (~/.claude.json):
{
"mcpServers": {
"transcription": {
"command": "uv",
"args": [
"--directory",
"/path/to/speechmatics_claude_code_mcp",
"run",
"python",
"server.py"
],
"env": {
"SPEECHMATICS_API_KEY": "your-api-key-here"
}
}
}
}Replace /path/to/speechmatics_claude_code_mcp with the actual path where you cloned the repo.
Note: Setting the API key in the env block is all you need. You don't need to export it separately or create a .env file.
4. Restart Claude Code
The transcription tools will now be available.
Available Tools
transcribe_file
Transcribe a single audio/video file.
Parameter | Type | Default | Description |
| string | required | Absolute path to the media file |
| string |
|
|
| boolean |
| Enable speaker diarization to identify different speakers |
| boolean |
| Include word-level timestamps (outputs JSON instead of TXT) |
| boolean |
| Re-transcribe even if a transcript already exists |
transcribe_directory
Transcribe all media files in a directory with parallel processing.
Parameter | Type | Default | Description |
| string | required | Path to directory containing media files |
| array |
| File extensions to include |
| string |
|
|
| boolean |
| Enable speaker diarization |
| boolean |
| Include word-level timestamps |
| boolean |
| Re-transcribe even if transcripts exist |
| boolean |
| Search subdirectories |
| integer |
| Maximum parallel transcription jobs (1-50) |
get_transcript
Read an existing transcript file.
Parameter | Type | Description |
| string | Path to media file OR transcript file |
get_usage
Get Speechmatics API usage statistics for the current month. No parameters required.
Output Formats
Transcripts are saved alongside the original media file.
Plain text (default): filename.transcript.txt
# Transcribed: 2024-01-30T14:32:00Z
# Source: meeting.mp4
# Duration: 12:34
# Accuracy: standard
# Diarization: true
S1: Hello everyone, welcome to the meeting.
S2: Thanks for having me.
...JSON with timestamps: filename.transcript.json
{
"metadata": {
"source": "meeting.mp4",
"transcribed_at": "2024-01-30T14:32:00Z",
"duration_seconds": 754,
"accuracy": "standard",
"diarization": true
},
"transcript": "S1: Hello everyone...",
"words": [
{"word": "Hello", "start": 0.0, "end": 0.5, "confidence": 0.98}
]
}Searching Transcripts
After transcribing, Claude can use its native Grep tool to search across all transcripts:
"Search all transcripts in ~/meetings for mentions of 'project deadline'"
"Find where we discussed the budget in the Q4 recordings"License
MIT
Available Tools
4 toolsget_transcriptC
Read an existing transcript file
Inputs: file_path (required).
get_usageA
Get Speechmatics API usage statistics for the current month
Inputs: no named parameters.
transcribe_directoryB
Transcribe all media files in a directory (parallel processing)
Inputs: directory (required), force, diarize, accuracy, +5 more.
transcribe_fileB
Transcribe a single audio/video file using Speechmatics API
Inputs: file_path (required), force, diarize, accuracy, +2 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Each tool has a distinct purpose: single-file transcription, batch transcription, reading a transcript, and viewing usage statistics. There is no overlap or ambiguity between the tools, even between transcribe_file and transcribe_directory, as their names clearly indicate the scope of operation.
All tool names follow a consistent verb_noun pattern: transcribe_file, transcribe_directory, get_transcript, get_usage. The verbs (transcribe, get) match the action performed, and the nouns clearly indicate the target. This makes the API predictable and easy to learn.
With just four tools, the server is tightly scoped to its purpose of transcription and transcript retrieval. Each tool is necessary and covers a distinct workflow step, leaving no feeling of bloat or missing essential functionality.
The core transcription workflow is fully covered: transcribing files (individually or in bulk), retrieving the resulting transcript, and checking account usage. There are no obvious gaps for the stated domain; optional operations like deleting or listing transcripts are not essential for the main use case.
Maintenance
Related MCP Connectors
Transcribe audio and video with Speechmatics speech-to-text from Claude and any MCP client.
Transcribe, summarize and analyze audio with AssemblyAI speech-to-text and Speech Understanding.
Transcribes audio and video files to text, SRT, VTT and timestamped chunks for RAG.
Transcribe audio and video files to text with timestamps and SRT or WebVTT subtitles
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