Submit and manage Forma (https://joinforma.com) claims from the command line and Model Context Protocol (MCP) clients
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"formanator": {
"command": "<see-readme>",
"args": []
}
}
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Submit and manage Forma (https://joinforma.com) claims from the command line and Model Context Protocol (MCP) clients
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[!NOTE] 🦀 Formanator is now built with Rust and distributed through Homebrew and Crates.io! v2.x, built in TypeScript and distributed through npm, is still available.
Formanator allows you to:
With the power of large language models 🧠👀 - free of charge thanks to GitHub Models - it can even analyse your receipts and generate your claims automatically.
brew tap timrogers/tap && brew install formanator
formanator crate by running cargo install formanator.formanator --help to check that everything is working and see the available commands.PATH (or $PATH on Unix-like systems), so you can execute it from your shell/terminal. For the best experience, call it formanator (or formanator.exe on Windows).formanator --help to check that everything is working.git clone https://github.com/timrogers/formanator
cd formanator
cargo install --path .
To infer claim details for PDF receipts, you need to have GraphicsMagick and Ghostscript installed.
# macOS
brew install graphicsmagick ghostscript
To get started, you'll need to connect Formanator to your Forma account:
formanator login.The access token is stored in ~/.formanatorrc.json (the same location used by the original Node.js implementation, so the two clients can share state).
When submitting a claim you can either provide every detail manually or let an LLM infer them. Two providers are supported:
GITHUB_TOKEN environment variable to a GitHub Personal Access Token with read access to GitHub Models, or pass --github-token.OPENAI_API_KEY environment variable, or pass --openai-api-key.If both are configured, Formanator prefers OpenAI.
formanator submit-claims-from-directory --directory input/
All .jpg, .jpeg, .png, .pdf and .heic receipts in the directory will be analysed by the LLM. You'll be asked to confirm the inferred claim details for each receipt before it's submitted, and successfully-submitted re