PDMT

PDMT – Pragmatic Deterministic MCP Templating is a high‑performance, deterministic templating engine that plugs directly into Model Context Protocol (MCP) workflows. It solves the problem of unreliable, non‑repeatable AI output by enforcing a zero‑temperature generation strategy: every request with the same input produces exactly the same content. This determinism is critical for audit trails, reproducible research, and any scenario where downstream systems must trust that the data they receive has not changed between runs.

At its core, PDMT exposes a template engine built on Handlebars with aggressive caching and validation. Developers can load predefined templates for structured artifacts—such as todo lists, documentation snippets, or configuration files—and feed them with rich data models. The engine guarantees that the resulting text is not only consistent but also adheres to predefined quality gates. By integrating with PMAT (Paiml MCP Agent Toolkit), PDMT automatically runs a suite of validators that check for actionability, complexity, time estimates, and circular dependencies in generated todo lists. This quality enforcement layer ensures that the content produced is actionable, realistic, and ready for immediate consumption by teams.

PDMT’s MCP integration is seamless: it implements the PMCP SDK, allowing AI assistants to discover and invoke PDMT as a tool or resource within their context. An assistant can request the generation of a structured todo list for a new project, and PDMT will return a deterministic JSON or Markdown output that can be parsed by downstream pipelines. The server also supports multiple output formats—YAML, JSON, Markdown, and plain text—making it adaptable to diverse tooling ecosystems.

Real‑world use cases include automated sprint planning, where an AI assistant translates high‑level user stories into a validated set of tasks with time estimates; compliance documentation generation, where deterministic outputs are required for regulatory audits; and continuous integration pipelines that need reproducible build scripts or configuration files. PDMT’s deterministic nature eliminates the “same prompt, different answer” problem, ensuring that automated workflows remain stable over time.

Unique advantages of PDMT are its extensive testing coverage (over 81 % with property and fuzz tests), its dependency analysis capabilities that detect circular references and compute critical paths, and the ability to enable or disable quality checks via feature flags. These attributes give developers fine‑grained control over the balance between speed and rigor, allowing PDMT to fit comfortably into both lightweight prototypes and mission‑critical production systems.