whisper-transcribe-mcp: Instructions file for Claude Code

CLAUDE.md

whisper-transcribe-mcp CLAUDE.md is an instructions file for Claude Code from ZahiriNatZuke/whisper-transcribe-mcp. It costs 666 tokens per session, scanned A, original, MIT.

Development instructions for whisper-transcribe-mcp, a Python MCP server that converts audio to text with either a local faster-whisper model or OpenAI’s Whisper API.

In plain words
What is it for?
Use them when developing, testing, running, or publishing the transcription server with Python, uv, or its release script.
Why use it?
They explain how to install, run, build, and release the server without having to infer the project setup.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions Claude Code.

This is ZahiriNatZuke/whisper-transcribe-mcp's own configuration. It tells Claude Code how to work on whisper-transcribe-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything whisper-transcribe-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ZahiriNatZuke/whisper-transcribe-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ZahiriNatZuke/whisper-transcribe-mcp/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/ZahiriNatZuke/whisper-transcribe-mcp

Made for: Claude Code.

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Per session 666 This file is loaded in full into every session.
When invoked 666 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00666 $0.00666
Opus 5.5 $0.00266 $0.00266
Sonnet 5.5 $0.00133 $0.00133
Haiku 4.5 $0.00067 $0.00067

Measured 1mo ago against content hash 6224cab1416b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

whisper-transcribe-mcp CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

whisper-transcribe-mcp is a Python MCP (Model Context Protocol) server that exposes audio transcription tools using either faster-whisper (local, offline) or the OpenAI Whisper API (cloud). Published on PyPI and consumed via uvx or pip.

Development Setup

# Install with all optional backends (recommended for development)
pip install -e ".[all]"

# Or with uv
uv pip install -e ".[all]"

Running the Server Locally

# Local backend
WHISPER_MODEL=base python -m whisper_transcribe.server

# OpenAI backend
OPENAI_API_KEY=sk-... python -m whisper_transcribe.server

Building and Publishing

# Build the package
python -m build

# Release a new version (bumps version in pyproject.toml, commits, pushes, creates GitHub release)
# PyPI publish is triggered automatically via GitHub Actions on release
./release.sh 1.2.3

Architecture

The entire server lives in a single file: whisper_transcribe/server.py.

  • Built on FastMCP (fastmcp>=3.2.0, the first release without known advisories), which handles MCP protocol, tool registration, and stdio transport.
  • Backend selection is determined at startup by the presence of OPENAI_API_KEY — there is no runtime switching.
  • The local WhisperModel is lazily loaded and cached in _local_model (module-level global), and reloaded only if the requested model_size changes.
  • transcribe_base64 delegates to transcribe_file after writing a temp file, then cleans it up.
  • Tool inputs (language, model_size, extension) are validated against allowlists before use; OpenAI errors are summarized (type + HTTP status) and the raw message only goes to stderr.

Optional dependency groups (pyproject.toml)

Extra Installs Enables
[local] faster-whisper Local CPU inference
[openai] openai OpenAI Whisper API
[all] both Auto-selects based on env

Read the full file on GitHub · 66 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago Changed · +2 lines · +65 tokens per session 6224cab1416b
  2. 2mo ago First seen · 64 lines · 601 tokens per session scan A 697541f3363a

Subscribe to this mod's changes

whisper-transcribe-mcp CLAUDE.md is an instructions file published in the GitHub repository ZahiriNatZuke/whisper-transcribe-mcp (0 stars, last pushed 5d ago), licensed MIT. It adds 666 tokens to every session, about $0.0027 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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