Pipelex: 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.

Get Started

• Quick Start — Sign up at app.pipelex.com, install the Pipelex plugin in Claude Code or Codex, and ask your agent for the method you want.
• Run It Yourself — Install the Pipelex runtime and run methods on your own machine.
• MTHDS Language Tutorial — Learn concepts, pipes, sequences, and structured outputs.
• Cookbook — Example methods you run by their address, each with a page showing every way to use it.

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.

[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 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.
• 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.
• Pipe Operators — LLM calls, document extraction, image generation, web search, composition, and custom functions.
• Pipeline Orchestration — Sequence, parallel, batch, and conditional controllers.
• 60+ AI Models — OpenAI, Anthropic, Mistral, Google, Deepseek, Hugging Face, and more.
• Validation and Dry Run — Catch errors without spending tokens.
• CLI and Tooling — Init, build, validate, run, and graph visualization.

The MTHDS Ecosystem

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

For AI agents: see /llms.txt for a machine-readable index of this documentation.

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