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Turn your expertise into an AI-powered App, MCP or API

Describe how the work gets done in plain English, and your coding agent builds it into a method with the Pipelex plugin. A method is a multi-step, deterministic AI procedure that chains LLMs, OCR, image generation and more. Then run it as a webapp for your team or as SaaS for your customers, as an MCP for chatbots, or via API for your software.

Quick Start Sign up at app.pipelex.com Cookbook

Get Started

  • Quick Start

    Sign up, install the Pipelex plugin in Claude Code or Codex, and ask your agent for the method you want — then run it from your chatbot, as a webapp, or via API.

  • Run It Yourself

    Install the Pipelex runtime and run methods from your terminal: on the hosted Pipelex API with one sign-in, or on your own machine against the model providers you choose.

  • MTHDS Language Tutorial

    Learn the declarative language step by step: concepts, pipes, sequences, inputs, and structured outputs.

  • Cookbook

    Example methods you run by their address, each with a page showing every way to use it: in your chatbot, in your code, as an app, or as a method of your own.

What a Method Looks Like

A method is a reusable, typed AI procedure, written in MTHDS, an open standard, and saved as a .mthds file. Each step is explicit, each output is structured, and every run is repeatable.

A single pipe in MTHDS — five lines that call an LLM with typed inputs and output:

[pipe.summarize_article]
type    = "PipeLLM"
inputs  = { article = "Text", audience = "Text" }
output  = "Text"
prompt  = "Summarize $article in three bullet points for $audience."

From here, Pipelex handles model routing across 60+ models, structured output parsing, and pipeline orchestration.

Why Methods?

  • Declarative

    Express business logic at a high level of abstraction, in human-readable .mthds files that work across models.

  • Typed

    Concepts are semantic types: AI understands what you mean, and every input and output connects with purpose.

  • Repeatable

    Deterministic orchestration that leaves exactly the room you want for AI to express its intelligence and creativity.

  • Composable

    Chain pipes into sequences, nest methods inside methods, and share them with the community.

Capabilities

  • Typed Concepts

    Semantic types that give meaning to every input and output — native, inline, or backed by Python classes.

  • Pipe Operators

    Operators that do the work: LLM calls, text structuring, document extraction, image generation, web search, composition, and custom functions.

  • Pipeline Orchestration

    Sequence, parallel, batch, and conditional controllers that wire pipes into full methods with shared working memory.

  • 60+ AI Models

    Your own provider keys for OpenAI, Anthropic, Mistral, Google, Deepseek, Hugging Face and more, or local models.

  • Validation and Dry Run

    Validate pipelines before execution and dry-run with mocked responses — catch errors without spending tokens.

  • CLI and Tooling

    Full CLI for init, build, validate, run, and graph visualization. Plus plxt for formatting and linting .mthds files.

The Ecosystem

MTHDS is the open standard behind Pipelex methods. It defines the language, the file format, and the ecosystem for sharing methods.

Explore the MTHDS ecosystem

  • mthds.ai — The MTHDS language specification
  • mthds.sh — The Methods Hub for discovering and sharing methods

Build and run methods with Pipelex

  • Pipelex plugin — The Pipelex plugin for Claude Code and Codex: skills that build and run methods, a hook that checks every edit, and the Pipelex tools
  • Pipelex MCP — The Pipelex MCP, which ChatGPT or Claude adds to run the methods saved in your account