OpenAI Agents SDK Integration

Expose all 47 Attestix tools natively to the OpenAI Agents SDK via MCPServerStdio. Production-ready in v0.3.0.

The OpenAI Agents SDK consumes Attestix as a native MCP server. All 47 tools are discovered automatically, with no per-tool wrapping.

Install

pip install attestix[openai-agents]

Verified against openai-agents SDK v0.14.x.

Minimal wiring

MCPServerStdio is an async context manager. Wrap it in async with so the server handle closes cleanly when the agent run ends.

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStdio

async def main():
    async with MCPServerStdio(
        name="Attestix",
        params={"command": "attestix", "args": ["mcp"]},
    ) as attestix:
        agent = Agent(
            name="quarterly-analyst",
            instructions="You are a financial analyst.",
            mcp_servers=[attestix],
        )
        result = await Runner.run(agent, input="Run Q4 analysis")
        print(result.final_output)

asyncio.run(main())

Restricting which tools are exposed

Use tool_filter with create_static_tool_filter to scope the Attestix tool surface for a given agent.

from agents.mcp import MCPServerStdio, create_static_tool_filter

attestix_filter = create_static_tool_filter(
    allowed_tool_names=[
        "create_agent_identity",
        "issue_credential",
        "record_training_data",
    ],
)

async with MCPServerStdio(
    name="Attestix",
    params={"command": "attestix", "args": ["mcp"]},
    tool_filter=attestix_filter,
    cache_tools_list=True,
) as attestix:
    agent = Agent(
        name="compliance-agent",
        mcp_servers=[attestix],
    )

Auto-issued audit entries

Every tool call made through the MCP server is appended to the Attestix hash-chained audit trail. No extra code needed on the SDK side.

Streaming and tool-use events

Runner.run_streamed returns a RunResultStreaming. Iterate its stream_events async iterator.

result = Runner.run_streamed(agent, input="Run Q4 analysis")
async for event in result.stream_events():
    if event.type == "run_item_stream_event" and event.name == "tool_called":
        print(event.item)

Audit-trail entries can be inspected after the run via the Attestix CLI or by calling the audit service directly in your own code.

HTTP transport

If the Attestix MCP server runs as a separate service, use MCPServerStreamableHttp (SDK v0.14 name). Wrap it in async with.

from agents.mcp import MCPServerStreamableHttp

async with MCPServerStreamableHttp(
    name="Attestix",
    params={"url": "http://localhost:8501/mcp"},
) as attestix:
    agent = Agent(
        name="quarterly-analyst",
        mcp_servers=[attestix],
    )

Start the Attestix MCP server in HTTP mode with:

attestix mcp --transport http --port 8501

Multi-agent orchestration

Wire Attestix into every agent in an orchestration so the entire graph is attestable. Role hand-offs are recorded as first-class audit events.

async with MCPServerStdio(
    name="Attestix",
    params={"command": "attestix", "args": ["mcp"]},
) as attestix:
    analyst = Agent(name="analyst", mcp_servers=[attestix])
    summarizer = Agent(name="summarizer", mcp_servers=[attestix])
    supervisor = Agent(
        name="supervisor",
        mcp_servers=[attestix],
        handoffs=[analyst, summarizer],
    )
    await Runner.run(supervisor, input="Prepare the Q4 board pack.")

UCAN delegations make the hand-off chain verifiable.

Sample repository

Full runnable example at github.com/VibeTensor/attestix/tree/main/examples.

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