agent-spawner

name	agent-spawner
domain	agent-tools
skill_type	skill
description	The `agent-spawner` skill provides the ability to dynamically create a new Pydantic AI agent configured with an external MCP server toolkit. This is extremely useful when an agent wants to spin up a sub-agent with specialized tools defined in an `mcp_config.json`, and interact with that agent immediately without modifying the parent agent's state or toolset.
license	MIT
tags	["agent","sub-agent","mcp","dynamic","spawner","pydantic-ai","orchestration"]
metadata	{"version":"1.2.1","author":"Genius"}

Agent Spawner Skill

The agent-spawner skill provides the ability to dynamically create a new Pydantic AI agent configured with an external MCP server toolkit. This is extremely useful when an agent wants to spin up a sub-agent with specialized tools defined in an mcp_config.json, and interact with that agent immediately without modifying the parent agent's state or toolset.

Usage

This skill includes a CLI script spawn_agent.py that utilizes agent_utilities.create_agent to build the agent and agent_utilities.chat to send it a prompt and wait for the response.

To use the tool, execute the script with the required arguments.

Examples

Spawning an Agent with a single Prompt:

python -m universal_skills.skills.agent-spawner.scripts.spawn_agent \
    --mcp-config ./references/example_mcp_config.json \
    --prompt "What tools are available to you?"

Spawning an Agent with a specific Name and System Prompt:

python -m universal_skills.skills.agent-spawner.scripts.spawn_agent \
    --mcp-config ./references/example_mcp_config.json \
    --prompt "Please execute a scan" \
    --name "SecurityScanner" \
    --system-prompt "You are a security scanning agent. Always use available tools."

Spawning an Agent using an MCP reference from mcp-client:

# This will automatically resolve 'servicenow-api.json'
# from universal_skills/skills/mcp-client/references/
python -m universal_skills.skills.agent-spawner.scripts.spawn_agent \
    --mcp-config servicenow-api.json \
    --prompt "What tools are available to you?"

Loading configuration from a .env file:

python -m universal_skills.skills.agent-spawner.scripts.spawn_agent \
    --dotenv .env \
    --mcp-config servicenow-api.json \
    --prompt "What tools are available to you?"

Available MCP Servers

You can easily connect to any of these pre-configured MCP servers by passing their JSON filename to the --mcp-config argument.

MCP Server	Config File	Description
ServiceNow	servicenow-api.json	ITSM and Workflow automation
GitLab	gitlab-api.json	DevOps platform for source control & CI/CD
Microsoft 365	microsoft-agent.json	Office 365, Outlook, OneDrive, Teams
Systems Manager	systems-manager.json	System administration and OS-level tools
Ansible Tower	ansible-tower-mcp.json	Automation controller for Ansible
Portainer	portainer-agent.json	Container management for Docker/K8s
Jellyfin	jellyfin-mcp.json	Media server management
Arr Stack	arr-mcp.json	Media management for PVRs (Sonarr, Radarr)
Container Manager	container-manager-mcp.json	Docker and container management
Nextcloud	nextcloud-agent.json	File sharing and collaboration server
Mealie	mealie-mcp.json	Recipe manager and meal planner
Repository Manager	repository-manager.json	Maintenance and management of git repos
Stirling PDF Agent	stirlingpdf-agent.json	PDF manipulation and processing
Wger Fitness	wger-agent.json	Fitness, workout, and diet tracking

Arguments

• --prompt: (Required) The instruction/prompt to send to the newly spawned agent.
• --mcp-config: Path to the mcp_config.json file configuring the capabilities. (Defaults to MCP_CONFIG env). If the file doesn't exist locally, it will automatically check for a matching reference in the mcp-client skill.
• --mcp-url: Alternative to config, a URL directly to a single MCP server. (Defaults to MCP_URL env).
• --custom-skills-directory: Path to directory to load custom Universal Skills. (Defaults to CUSTOM_SKILLS_DIRECTORY env).
• --dotenv: Path to a .env file to load environment variables from.
• --name: The name of the spawned agent. (Defaults to DEFAULT_AGENT_NAME env).
• --system-prompt: The system prompt to apply. (Defaults to AGENT_SYSTEM_PROMPT env).
• --provider: The LLM Provider to use inside the agent (e.g. openai, anthropic). (Defaults to PROVIDER env).
• --model-id: The model identifier. (Defaults to MODEL_ID env).
• --base-url: LLM Base URL for API calls. (Defaults to LLM_BASE_URL env).
• --api-key: API key for the LLM. (Defaults to LLM_API_KEY env).
• --insecure: Disable SSL verification for MCP and LLM calls.

Implementation Details

The script depends on agent_utilities which must be installed in the environment. It loads the MCP servers defined in the config file, instantiates a Pydantic AI agent with those MCP servers, and uses the chat method to dispatch the user's prompt to the newly formed agent.