Agent Registry — OpenAI Agents SDK

Wire a LumoAuth-registered agent into the OpenAI Agents SDK. The agent's identity is its registered AGENT_CLIENT_ID; it authenticates via OAuth 2.0 client credentials (via LumoAuthAgent); tools check has_capability(...) before running; MCP (Model Context Protocol, the standard way agents call tool servers) tools swap the base access token for one bound to the MCP server using token exchange.

Prerequisites

Install the lumoauth package and set the environment variables LUMOAUTH_URL, LUMOAUTH_ORG_ID, AGENT_CLIENT_ID, and AGENT_CLIENT_SECRET. See Install the SDK.

Install

pip install lumoauth openai-agents

Example

import asyncio
from agents import Agent, Runner, function_tool
from lumoauth import LumoAuthAgent

# 1. Initialize and authenticate the LumoAuth Agent
lumo_agent = LumoAuthAgent()
lumo_agent.authenticate()

# 2. Define tools that check LumoAuth capabilities
@function_tool
def search_company_documents(query: str) -> str:
    """Search internal company documents for the given query."""
    if not lumo_agent.has_capability('read:documents'):
        return "Error: Agent lacks 'read:documents' capability."
    return f"Found 3 documents matching '{query}'"

@function_tool
def query_financial_mcp(metric: str) -> str:
    """Query the secured financial metrics MCP server for a given metric."""
    if not lumo_agent.has_capability('mcp:financial'):
        return "Error: Agent lacks 'mcp:financial' capability."
    mcp_token = lumo_agent.get_mcp_token("urn:mcp:financial-data")
    if not mcp_token:
        return "Error: Failed to obtain token for Financial MCP server."
    return f"Retrieved {metric}: $1.2M (Authenticated via MCP Token Exchange)"

# 3. Check budget before running
if lumo_agent.is_budget_exhausted():
    raise RuntimeError("Agent budget exhausted for today.")

# 4. Create the OpenAI Agent
research_agent = Agent(
    name="Research Analyst",
    instructions="You are a senior analyst. Use tools to search documents and query financial metrics.",
    tools=[search_company_documents, query_financial_mcp],
)

# 5. Run the agent
async def main():
    result = await Runner.run(
        research_agent,
        "Search documents for Q3 performance, then query the financial MCP for EBITDA.",
    )
    print(result.final_output)

if __name__ == "__main__":
    asyncio.run(main())

How it works

Step	What happens
LumoAuthAgent()	Reads credentials from env vars and initializes the client
lumo_agent.authenticate()	Runs the OAuth 2.0 client-credentials flow
@function_tool	Decorates plain Python functions as OpenAI SDK tools
has_capability(...)	Guards tool execution with LumoAuth capability checks
get_mcp_token(...)	Swaps the agent token for an MCP-specific token (token exchange)

Next steps

• Agent Registry overview — manage registrations, budgets, and capabilities
• JIT Permissions — OpenAI Agents SDK — add just-in-time permission escalation

Standards used on this page

Plain name	Standard
Token exchange (delegation)	RFC 8693

See the standards reference for what each one covers and how LumoAuth uses it.