# AgentTasker MCP Server

> Use this tool when you need to execute multiple tasks in parallel using AI agents, solving problems of scalability and efficiency in task management. The AgentTasker MCP Server takes standard input and output, allowing for seamless integration with AI agents. It is ideal for use cases requiring distributed task processing, such as data processing, machine learning, and automation workflows.

Canonical page: https://skillsregistry.net/skills/io-github-s3brr-agent-tasker-mcp  
JSON: https://api.skillsregistry.net/v1/skills/io-github-s3brr-agent-tasker-mcp

## Description

Minimal stdio MCP server for parallel task execution by AI agents.

## Trust

- **Trust score (0–1):** 0.75
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.S3bRR%2Fagent-tasker-mcp)
- **Repository:** <https://github.com/S3bRR/agent-tasker-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": "io-github-s3brr-agent-tasker-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-s3brr-agent-tasker-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-s3brr-agent-tasker-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