# awesome-mineflayer-mcp

> Use this tool when you need to control a Minecraft bot programmatically, automating tasks such as movement, crafting, and combat. It solves problems in Minecraft automation, bot management, and integration with large language models (LLMs) by providing a comprehensive set of 110 strongly-typed tools. It accepts input commands and outputs event streams, making it ideal for use cases requiring fine-grained control over Minecraft interactions.

Canonical page: https://skillsregistry.net/skills/g0osey99-awesome-mineflayer-mcp  
JSON: https://api.skillsregistry.net/v1/skills/g0osey99-awesome-mineflayer-mcp

## Description

A production-ready MCP server that gives an LLM agent standalone-equivalent control over a Mineflayer Minecraft bot — movement, mining, crafting, inventory, combat, containers, chat, and much more — exposed as 110 strongly-typed tools across 23 groups, with full bot lifecycle management and dual (poll + push) event streaming.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/l8nsohup8j)
- **Repository:** <https://github.com/G0Osey99/awesome-mineflayer-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": "g0osey99-awesome-mineflayer-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/g0osey99-awesome-mineflayer-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/g0osey99-awesome-mineflayer-mcp/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