# Nano Agent

> Use this tool when you need to execute complex tasks and file operations through natural language prompts, leveraging AI agents with access to multiple LLM providers. It solves problems related to automating multi-step coding tasks, file manipulation, and project automation, providing a powerful interface for task execution. The Nano Agent accepts plain English task descriptions as input and outputs executed tasks, making it ideal for developers seeking to delegate tasks to AI agents through conversational interfaces.

Canonical page: https://skillsregistry.net/skills/disler-nano-agent  
JSON: https://api.skillsregistry.net/v1/skills/disler-nano-agent

## Description

Nano Agent MCP server by IndyDevDan that bridges the Model Context Protocol with OpenAI's Agent SDK to enable autonomous agent execution through natural language prompts. The implementation provides a single powerful tool that accepts task descriptions in plain English and executes them using an AI agent with file system access, supporting multiple LLM providers including OpenAI (GPT-5 models), Anthropic (Claude models), and local Ollama models. Features comprehensive file operations (read, write, edit, list directories), multi-provider configuration with automatic API key detection, token tracking and cost calculation, and includes Claude Code integration with hooks for session management, TTS notifications, and transcript logging, making it valuable for developers who want to delegate complex multi-step coding tasks, file manipulation, and project automation to AI agents through conversational interfaces.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/disler-nano-agent)
- **Repository:** <https://github.com/disler/nano-agent>

## 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": "disler-nano-agent"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/disler-nano-agent` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/disler-nano-agent/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