# Prolog

> Use this tool when you need to leverage logical programming capabilities in AI interactions, solving problems that require reasoning and inference, such as expert systems, knowledge graphs, and decision support systems. It takes Prolog programs and queries as input and outputs structured solutions, providing a bridge between AI assistants and Prolog's capabilities. Ideal for use cases where logical deductions and rule-based reasoning are necessary, such as natural language processing, semantic web, and artificial intelligence applications.

Canonical page: https://skillsregistry.net/skills/snoglobe-prolog  
JSON: https://api.skillsregistry.net/v1/skills/snoglobe-prolog

## Description

Prolog MCP provides tools for executing Prolog programs, running queries, and discovering available predicates within a Prolog engine. Built using Go and the ichiban/prolog library, this implementation creates a bridge between AI assistants and Prolog's logical programming capabilities through three main tools: executing programs, running time-limited queries with solution collection, and exploring the predicate environment. The server handles query timeouts gracefully and formats solutions as structured data, making it useful for developers who want to leverage Prolog's reasoning capabilities directly from their AI assistant interactions.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/snoglobe-prolog)
- **Repository:** <https://github.com/snoglobe/prolog_mcp>

## 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": "snoglobe-prolog"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/snoglobe-prolog` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/snoglobe-prolog/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