# freellmpool

> Use this tool when you need to access and manage multiple Large Language Model (LLM) providers through a single interface, allowing you to ask questions, manage quotas, and route requests to various models. It solves problems of LLM provider fragmentation and simplifies model management by pooling 18 providers. The tool accepts input requests and returns output responses, providing features like panel, tokenmax, and stats for efficient LLM utilization.

Canonical page: https://skillsregistry.net/skills/io-github-0xzr-freellmpool  
JSON: https://api.skillsregistry.net/v1/skills/io-github-0xzr-freellmpool

## Description

Pool 18 LLM providers through MCP: ask, panel, tokenmax, route, models, quota, and stats.

## Trust

- **Trust score (0–1):** 0.56
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 0.11.4
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.0xzr%2Ffreellmpool)
- **Repository:** <https://github.com/0xzr/freellmpool>

## 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": "io-github-0xzr-freellmpool"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-0xzr-freellmpool` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-0xzr-freellmpool/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