Frenchie

io.github.Lab94Published by GitHub account Lab94v0.5.0Updated Oct 24, 2026

OCR, transcription, file extraction, and image generation for AI agents via MCP.

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Overview

AI-generated overview

Frenchie converts PDFs, images, audio, video and Office files to Markdown and generates images, using a paid credit-based cloud service.

What you can do
Convert PDFs and images into Markdown text via OCR, with an optional language hint for accuracy and auto-saved results in local mode. Transcribe audio and video files into Markdown transcripts, with optional ISO language codes or auto-detection. Extract DOCX, XLSX, CSV, TSV and PPTX documents into Markdown, saved to a local folder or returned inline. Generate a single image from a text prompt with optional style, size, quality, format and background settings. Upload files to get presigned URLs and fetch temporary download links for result files in the hosted HTTP mode. Retrieve the latest result of an asynchronous processing job.
When to use it
Useful when an assistant needs to read scanned PDFs, images, meeting recordings or Office documents as Markdown, or to produce a quick image from a prompt. Best for agents that already handle files and want multimodal conversion without building their own OCR or transcription pipeline.
Requirements
Runs either as a hosted endpoint at mcp.getfrenchie.dev or as a local npm package started with npx, which needs Node.js. Requires a Frenchie account and API key, supplied as FRENCHIE_API_KEY or an Authorization bearer header. An optional default language can be set via FRENCHIE_DEFAULT_LANGUAGE or the X-Frenchie-Default-Language header. Network access is needed for all processing.
Before you install
Processing consumes paid credits: OCR 1 per page, transcription 2 per minute, extraction 0.5 to 1 per page or slide, image generation 20 per image, with 100 free credits on first signup. Files are uploaded to a third-party service; results expire about 30 minutes after delivery, so save Markdown promptly. The API key is a secret written into agent config files by the installer.

Installation

In SourceWeft

  1. Open Frenchie in the dashboard and add it to a workspace.
  2. Connect Authorization token credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.Lab94%2Ffrenchie-skill/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "frenchie": {
      "type": "http",
      "url": "https://mcp.getfrenchie.dev/",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

README

[Frenchie — your agent's best friend.]

[smithery badge]

@lab94/frenchie

Frenchie — your agent's best friend.

Install Frenchie in your coding agent with one command. Frenchie Kit gives agents file and multimodal capabilities: read PDFs and images, transcribe audio and video, extract Office/CSV files to Markdown, and generate images from text prompts. Frenchie Method gives teams a structured workflow from requirement to release.

Upgrading from 0.1.x or 0.2.x? See MIGRATION.md for the breaking changes in 0.3.0 (stdio metadata-only responses, absolute-path MCP configs, new mcp --help / --selftest flags).

This package ships:

  • Frenchie Kit (/ocr, /transcribe, /extract, /generate-image, /frenchie-status commands + HTTP/stdio MCP guidance)
  • Frenchie Method (/frenchie-method, /requirement, /qa-analysis, /implement, /run-test, /pr-review, /release-check, and related workflow commands)
  • The Frenchie stdio MCP server (lab94-frenchie mcp) bundled for npx
  • An installer that wires skills and MCP config into your agent

Quick start

1. Install the skills

From the root of your project:

bash
npx @lab94/frenchie install

This installs Frenchie Kit and Frenchie Method skills. Method is text-only and works without an API key.

Optional Method config:

bash
npx @lab94/frenchie install --init-method

This creates .frenchie/method.config.json and .frenchie/.gitignore; it does not edit your root .gitignore.

2. Log in for Kit MCP tools when you need file or image capabilities

Create an account at getfrenchie.dev. You get 100 free credits on your first signup, once per email. No card required.

Then connect your local agent:

bash
npx @lab94/frenchie login

The login command opens a browser device-code flow, then writes FRENCHIE_API_KEY into the MCP config the installer created. The full key is never printed.

Fallback if you already have a key from the dashboard:

bash
npx @lab94/frenchie install --api-key fr_your_key_here

To target a specific agent:

bash
npx @lab94/frenchie login --agent claudenpx @lab94/frenchie login --agent cursornpx @lab94/frenchie login --agent codexnpx @lab94/frenchie login --agent vscodenpx @lab94/frenchie login --agent gemini

User-level installs (Antigravity, Windsurf, Zed, Claude Desktop) need the --global flag — auto-detect never writes under $HOME:

bash
npx @lab94/frenchie login --agent antigravity   --globalnpx @lab94/frenchie login --agent windsurf       --globalnpx @lab94/frenchie login --agent zed            --globalnpx @lab94/frenchie login --agent claude-desktop --global

Fallback with an existing key:

bash
npx @lab94/frenchie install --agent claude        --api-key fr_…npx @lab94/frenchie install --agent codex         --api-key fr_…npx @lab94/frenchie install --agent antigravity   --global --api-key fr_…npx @lab94/frenchie install --agent claude-desktop --global --api-key fr_…

After login, your agent can call ocr_to_markdown, transcribe_to_markdown, extract_to_markdown, or generate_image. OCR/transcription/extraction results are saved to .frenchie/<name>/result.md automatically; generated images are saved to .frenchie/<slug>/generated.<ext>.

Upgrading later

When a new Frenchie version ships, the pinned package spec inside each MCP config (@lab94/[email protected]) needs to point at the new version so npx stops serving a cached older bundle. Two upgrade commands cover everything:

bash
# Project-scoped configs in this directory (.mcp.json, .cursor/mcp.json, .codex/config.toml, etc.)npx @lab94/frenchie@latest install
# Every $HOME config that already has a frenchie entry — Antigravity, Claude Desktop, Windsurf, Zed,# and any global Claude Code / Cursor / Codex / Gemini configs you set up. cwd doesn't matter.npx @lab94/frenchie@latest install --global

install --global is upgrade-mode: it only rewrites frenchie entries that already exist. It will not surprise-install anything new under $HOME. First-time global installs still go through install --agent <name> --global.

3. Restart your agent

The installer prints the restart hint for your agent. After that, ask:

OCR ./report.pdf with Frenchie

…and Frenchie takes it from there.

For workflow orchestration, ask:

txt
/frenchie-method

/frenchie remains the Kit entrypoint in agents that use a single Frenchie command. It is not an alias for Method.

Hosted agents (Lovable, Manus, Claude.ai, ChatGPT.com, Le Chat)

These agents can't run local npm binaries. Use the hosted MCP endpoint instead:

URL:    https://mcp.getfrenchie.devHeader: Authorization: Bearer fr_your_key_here

The same @lab94/frenchie skill files work in HTTP mode — install them once with install --agent <name> and the included SKILL.md will tell the agent to upload files via upload_file before calling OCR/transcription/extraction. Image generation does not need an upload step in HTTP mode; it returns a short-lived imageUrl that the agent should download for the user.

What you get

Frenchie Kit

CommandWhat it does
/ocr <file>Parse a PDF or image into Markdown
/transcribe <file>Parse audio or video into a Markdown transcript
/extract <file>Parse DOCX, XLSX, CSV, TSV, or PPTX into Markdown
/generate-image <prompt>Generate a single image from a text prompt
/frenchie-statusCheck credits and recent jobs

Under the hood, Frenchie exposes these MCP tools:

  • ocr_to_markdown
  • transcribe_to_markdown
  • extract_to_markdown
  • generate_image
  • get_job_result
  • upload_file (HTTP mode only)
  • fetch_result_file (HTTP mode only)

Frenchie Method

Slash notation is the canonical Method command name. Claude Code reads command files directly. Codex Desktop gets the same entries through wrapper skills such as requirement and qa-analysis; restart Codex after install before trying /requirement. Hosts without slash support can use natural language such as Frenchie Method requirement ....

CommandWhat it does
/frenchie-methodRoute a task through Method from requirement to release
/method-checkValidate Method config, artifacts, gates, and next action
/requirementTurn a request into scoped requirements
/qa-analysis / /test-caseDesign proof before implementation planning
/sa-analysis / /implementation-planAnalyze architecture and implementation approach
/implementExecute from Method artifacts using the current agent
/run-testRun repo-declared verification and write a test report
/pr-review / /review-prReview the result, tests, security, and artifact drift
/release-checkRead-only release readiness gate

Method stores optional workflow artifacts under .frenchie/docs/feature/. install --init-method also writes a visible skillTriggers skeleton in .frenchie/method.config.json; command keys are empty slots teams can fill with installed agent skills, for example "requirement": ["brainstorming"]. Teams decide whether to commit or ignore Method config and artifacts.

Invocation — how to call Frenchie in each agent

Every agent handles MCP a little differently. /ocr is a Claude Code-only slash command; Method slash commands are host-dependent and use Codex wrapper skills outside Claude Code. Other agents use natural language, @-mention, or a server-name slash command. All facts below are dogfood-verified.

AgentInvokeFull guide
Claude Code/ocr TOR.pdfdocs
CursorUse Frenchie to OCR TOR.pdfdocs
Codex (Desktop / CLI / IDE)Kit: /frenchie TOR.pdf · @frenchie ocr TOR.pdf; Method: /requirement after restart, or Frenchie Method requirement ...docs
Antigravity/frenchie TOR.pdf (invokes by server name)docs
VS Code Copilot/frenchie TOR.pdfdocs
Claude DesktopUse Frenchie to OCR TOR.pdfdocs
WindsurfOCR TOR.pdf via Frenchiedocs
Gemini CLIOCR TOR.pdf with Frenchiedocs
ZedOCR TOR.pdf via Frenchiedocs

Something not working? See the symptom-first troubleshooting guide — every error we've hit in dogfood has a canonical entry.

Pricing

Simple numbers. No subscriptions.

File extraction pricing: DOCX 0.5 credits per page, XLSX 0.5 credits per sheet, CSV/TSV 0.5 credits per file, PPTX 1 credit per slide.

ActionCost
OCR1 credit per page
Transcription2 credits per minute
DOCX extraction0.5 credits per page
XLSX extraction0.5 credits per sheet
CSV/TSV extraction0.5 credits per file
PPTX extraction1 credit per slide
Image generation20 credits per image

$1 = 100 credits. Credits don't expire.

Privacy

Files are processed and deleted. Results expire about 30 minutes after first delivery. If you need a durable copy, save the Markdown when it comes back.

Supported formats

OCR: PDF, PNG, JPG, JPEG, WebP

Transcription: MP3, M4A, WAV, MP4, MOV, WebM

File extraction: DOCX, XLSX, CSV, TSV, PPTX

Image generation: PNG, JPEG, WebP output from text prompts

Need help?

Source: README.md at commit 91ba927

Tools

7

ocr_to_markdown

OCR to Markdown

Convert PDF/image files into Markdown through Frenchie

Parametersapi_keyfile_pathuploaded_file_reference

transcribe_to_markdown

Transcribe to Markdown

Convert audio/video files into Markdown transcripts through Frenchie. Set language (ISO 639-1 code, e.g. 'th', 'en', 'ja') for better accuracy; omit for auto-detection.

Parametersapi_keylanguagefile_pathuploaded_file_reference

generate_image

Generate Image

Generate a single image from a text prompt through Frenchie. Required: prompt. Optional: style (free-text style direction), size, quality, format, background. stdio mode auto-saves the image to .frenchie/<slug>/generated.<ext>; HTTP mode returns a presigned imageUrl that the agent should download for the user.

Parameterssizestyleformatpromptrequiredapi_keyqualitybackgroundoutput_dir

extract_to_markdown

Extract to Markdown

Extract structured documents (.docx, .xlsx, .csv, .tsv, .pptx) into Markdown through Frenchie. stdio mode auto-saves the result to .frenchie/<name>/result.md; HTTP mode returns inline Markdown.

Parametersapi_keyfile_pathuploaded_file_reference

get_job_result

Get Job Result

Fetch the latest async Frenchie job result

Parametersjob_idrequiredapi_key

upload_file

Upload File (HTTP)

Get a presigned upload URL for use with ocr_to_markdown, transcribe_to_markdown, or extract_to_markdown in HTTP mode. After calling this tool, PUT the file to upload_url (with the correct Content-Type header), then pass object_key as uploaded_file_reference to the processing tool.

Parametersapi_keyfilenamerequiredfile_sizerequiredmime_typerequired

fetch_result_file

Fetch Result File (HTTP)

Get a temporary download URL for a result file from OCR/transcription output. Use this to download images referenced as frenchie-result: in the result markdown.

Parametersapi_keyobject_keyrequired

Version history

1
  1. v0.5.0LatestSep 16, 2026

Score

100% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts