TranscriptionTools MCP Server
@MushroomFleet
About TranscriptionTools MCP Server
MCP server for transcript processing — formatting, contextual repair & smart summarization with deep-thinking LLMs
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"TranscriptionTools-MCP": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@MushroomFleet/transcriptiontools-mcp",
"--client",
"claude"
]
}
}
}Tools
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Overview
What is TranscriptionTools MCP Server?
TranscriptionTools MCP Server is a Model Context Protocol server that provides intelligent transcript processing, including natural formatting, contextual repair, and smart summarization powered by Deep Thinking LLMs. It is aimed at users needing to clean, format, and summarize spoken-language transcripts.
How to use TranscriptionTools MCP Server?
Install by cloning the repository, running npm install and npm run build, then configure the server in your MCP settings file. Invoke the tools repair_text, get_repair_log, format_transcript, and summary_text via the MCP client interface.
Key features of TranscriptionTools MCP Server
- Four MCP tools for transcript processing: repair, log, format, summary
repair_textcorrects transcription errors with >90% confidenceformat_transcriptremoves timestamps and applies intelligent spacingsummary_textgenerates summaries with time, word, or character constraintsget_repair_logretrieves detailed logs of previous repairs
Use cases of TranscriptionTools MCP Server
- Correcting errors and awkward phrasing in raw automated transcripts
- Converting timestamped meeting or interview transcripts into natural prose
- Generating concise, constraint-based summaries of lengthy transcriptions
- Auditing all changes made during a repair session via repair logs
FAQ from TranscriptionTools MCP Server
What are the system requirements?
Node.js and npm are required to build and run the server. The server is written in TypeScript and compiles to JavaScript.
What runtime or LLM does it depend on?
The README mentions “Deep Thinking LLMs” but does not specify a particular model or API; the server appears to use its own logic for repair and formatting without requiring an external LLM service.
Where does transcript data live?
Data is passed directly as input text or file paths; the server does not store transcripts externally unless the user provides file paths on the local filesystem.
What transport or authentication does it use?
The server uses standard MCP stdio transport; no authentication or remote endpoints are described in the README.
Does it ever modify the original audio?
No. The contextual repair feature explicitly states “No original audio required” – it works only on the text transcript.
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