# pypddlengine

> Use this tool when you need to interactively explore PDDL planning problems, enabling AI agents to initialize, execute actions, inspect states, and check goals. It solves problems related to planning and decision-making by providing a PDDL engine as MCP tools, allowing for flexible and dynamic exploration of planning scenarios. Ideal for use cases requiring iterative planning, debugging, and optimization of PDDL-based planning problems.

Canonical page: https://skillsregistry.net/skills/kgoe-ait-pypddlengine  
JSON: https://api.skillsregistry.net/v1/skills/kgoe-ait-pypddlengine

## Description

Enables AI agents to interactively explore PDDL planning problems by exposing a PDDL engine as MCP tools for initialization, action execution, state inspection, and goal checking.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ktlk9jw3qq)
- **Repository:** <https://github.com/AIT-Complex-Dynamical-Systems/pypddlengine>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "kgoe-ait-pypddlengine"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kgoe-ait-pypddlengine` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kgoe-ait-pypddlengine/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt