kcli/a2as.yaml at main · karmab/kcli · GitHub

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manifest:
  version: "0.1.3"
  schema: https://a2as.org/cert/schema
  subject:
    name: karmab/kcli
    source: https://github.com/karmab/kcli
    branch: main
    commit: "a14f2258"
    scope: [extras/chatbot.py, kvirt/agent/agent/__init__.py]
  issued:
    by: A2AS.org
    at: '2026-02-11T16:30:16Z'
    url: https://a2as.org/certified/agents/karmab/kcli
  signatures:
    digest: sha256:cPXksFGTRU6_hXoCv_98hKZvsJnr1bH80lz6poklaus
    key: ed25519:SkTLhxcJtWqN7YbN0xhawQkp5TJCiir28kiaRnC9ecM
    sig: ed25519:aLlbnOgr11E44YL3HJ-NRzSWQLHc2zWGvX5zJBKPsdi_szbmK6l6paq8DPNas6xSP7gMxae7LhMf1fSduwqlDg

agents:
  root_agent:
    type: instance
    models: [gemini-2.5-flash]
    tools: [tools]
    mcp: [tools]
    params:
      name: kcli_agent
      description: Manages VMs and Kubernetes clusters using kcli
      instruction: [You are a helpful assistant that can manage virtual machines and kubernetes cluster on, any virtualization
          and cloud provider using the provided tools for this purpose.]

models:
  gemini-2.5-flash:
    type: literal
    agents: [root_agent]
    params:
      alias: [openai/gemini-2.5-flash]

tools:
  tools:
    type: mcp
    agents: [root_agent]
    params:
      class: McpToolset
      mcp_server: tools

mcp:
  tools:
    type: process
    agents: [root_agent]
    params:
      class: McpToolset
      connection_type: StdioConnectionParams
      command: python3
      args: [MCP_PATH]
      timeout: "120"

imports:
  Agent: google.adk.agents.llm_agent.Agent
  AgentCard: a2a.types.AgentCard
  AgentSkill: a2a.types.AgentSkill
  ast: ast
  asyncio: asyncio
  ChatOpenAI: langchain_openai.ChatOpenAI
  ClientSession: mcp.ClientSession
  create_react_agent: langgraph.prebuilt.create_react_agent
  LiteLlm: google.adk.models.lite_llm.LiteLlm
  load_mcp_tools: langchain_mcp_adapters.tools.load_mcp_tools
  McpToolset: google.adk.tools.mcp_tool.mcp_toolset.McpToolset
  os: os
  stdio_client: mcp.client.stdio.stdio_client
  StdioConnectionParams: google.adk.tools.mcp_tool.mcp_session_manager.StdioConnectionParams
  StdioServerParameters: mcp.StdioServerParameters
  sys: sys
  to_a2a: google.adk.a2a.utils.agent_to_a2a.to_a2a
  uvicorn: uvicorn
  warnings: warnings
  which: shutil.which

functions:
  get_skills:
    type: sync
    module: kvirt.agent.agent
  main:
    type: sync
    module: kvirt.agent.agent
  main_chat:
    type: async
    module: extras.chatbot

variables:
  GOOGLE_API_KEY:
    type: env
    params:
      caller: [os.getenv]
      path: [kvirt.agent.agent]
  IP:
    type: env
    params:
      caller: [os.getenv]
      path: [kvirt.agent.agent]
  MODEL:
    type: env
    params:
      caller: [os.getenv, os.environ]
      path: [kvirt.agent.agent]
  OLLAMA_API_BASE:
    type: env
    params:
      caller: [os.getenv]
      path: [kvirt.agent.agent]
  OPENAI_API_BASE:
    type: env
    params:
      caller: [os.getenv]
      path: [kvirt.agent.agent]
  OPENAI_API_KEY:
    type: env
    params:
      caller: [os.environ]
  PORT:
    type: env
    params:
      caller: [os.getenv]
      path: [kvirt.agent.agent]
  VLLM_API_BASE:
    type: env
    params:
      caller: [os.getenv]
      path: [kvirt.agent.agent]

files:
  MCP_PATH:
    type: variable
    actions: [read]
    params:
      caller: [open]

processes:
  kmcp.py:
    type: mcp
    actions: [exec]
    params:
      caller: [StdioServerParameters]
      shell: ["False"]
  python3:
    type: mcp
    actions: [exec]
    params:
      caller: [StdioServerParameters]
      shell: ["False"]

networks:
  "127.0.0.1":
    type: api
    actions: [GET]
    urls: [/v1]
    protocols: [http]
    ports: ["4000"]
    params:
      links: [base_url]
  agent_card:
    type: api
    actions: [GET]
    protocols: [http]
    ports: ["80"]
    params:
      caller: [AgentCard]
      pattern: http://{IP}:{PORT}