# Fetchium

> Use this tool when you need to efficiently retrieve web data for AI agents, solving problems of token limitations and excessive request volumes. Fetchium provides token-efficient web retrieval, allowing for optimized data extraction and processing. It takes in AI agent requests and outputs relevant web data, ideal for use cases where data retrieval needs to be fast, reliable, and cost-effective.

Canonical page: https://skillsregistry.net/skills/zuhabul-fetchium  
JSON: https://api.skillsregistry.net/v1/skills/zuhabul-fetchium

## Description

Fetchium — token-efficient web retrieval for AI agents

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-06-12

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/kc6ovgv2d9)
- **Repository:** <https://github.com/zuhabul/Fetchium>

## 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": "zuhabul-fetchium"
    }
  }
}
```

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