Meta Tools provide dynamic tool discovery and execution capabilities for Python applications, allowing your AI agents to explore and use tools at runtime.
Meta Tools are currently in Beta. The API may change in future versions.

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Quick Start

from stackone_ai import StackOneToolSet

# Initialize the toolset
toolset = StackOneToolSet()

# Get tools for your account
all_tools = toolset.get_tools("*", account_id="your_account_id")

# Get meta tools for dynamic discovery
meta_tools = all_tools.meta_tools()

# Search for relevant tools
search_tool = meta_tools.get_tool("meta_search_tools")
result = search_tool.call(
    query="manage employees create update list",
    limit=5,
    minScore=0.3
)

print("Found tools:")
for tool in result.get("tools", []):
    print(f"- {tool['name']} (score: {tool['score']:.2f})")

# Execute a discovered tool
execute_tool = meta_tools.get_tool("meta_execute_tool") 
if result.get("tools"):
    best_tool = result["tools"][0]
    execution_result = execute_tool.call(
        tool_name=best_tool["name"],
        params={"limit": 10}
    )
    print(f"Result: {execution_result}")

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Core Functions

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meta_search_tools

Search for relevant tools based on natural language queries: 
search_tool = meta_tools.get_tool("meta_search_tools")
result = search_tool.call(
    query="employee time off management",
    limit=3,
    minScore=0.4
)

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meta_execute_tool

Execute any tool dynamically by name: 
execute_tool = meta_tools.get_tool("meta_execute_tool")
result = execute_tool.call(
    tool_name="hris_list_employees", 
    params={"department": "engineering", "limit": 20}
)

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Framework Integration

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LangChain

from langchain_openai import ChatOpenAI

# Convert to LangChain tools
langchain_tools = meta_tools.to_langchain()
model = ChatOpenAI(model="gpt-4o-mini")
model_with_tools = model.bind_tools(langchain_tools)

response = model_with_tools.invoke(
    "Find employee management tools and list recent hires"
)

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CrewAI

from crewai import Agent

# Convert to CrewAI tools
crewai_tools = meta_tools.to_crewai()

hr_agent = Agent(
    role="HR Assistant",
    goal="Help with employee management tasks",
    tools=crewai_tools,
    verbose=True
)

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Best Practices

  1. Cache Tool Searches: Store search results to avoid repeated API calls
  2. Handle Failures: Meta tools may fail if integrations are unavailable
  3. Use Specific Queries: More specific searches return better results
  4. Validate Parameters: Check tool parameters before execution
  5. Set Reasonable Limits: Don’t search for too many tools at once

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Next Steps