How to Use the Cerbos (Access Control) MCP in AutoGen

Q: How do AutoGen agents collaborate to update policies in Cerbos (Access Control)?

One agent drafts the policy using addpolicy, while a security agent reviews it. They debate the changes in a conversation loop until they reach consensus, then apply it.

Q: Can AutoGen run health checks on Cerbos (Access Control)?

Yes. Agents use gethealth and getserverinfo to monitor the Cerbos instance. If the system is unhealthy, a monitoring agent can notify your team or route requests elsewhere.

Q: How do I register Cerbos (Access Control) tools in AutoGen?

Use the autogen-ext package to connect to the MCP Server over HTTP or stdio. Pass the adapter-generated tools list directly into your AssistantAgent constructor.

Q: How does AutoGen handle complex query planning?

The agents use the planresources tool to get the AST for filtering resources. They then translate this AST into database queries to enforce data isolation at the database level.

Let AutoGen agents debate policy changes and verify access security before deploying rules to Cerbos.

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Setup Cerbos (Access Control) with AutoGen

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Multi-agent consensus on policy updates

The `add_policy` tool runs over an MCP connection, allowing your AutoGen agents to write new access rules to your Cerbos instance. Before applying the changes, a security agent runs a debate with a developer agent to verify the policy doesn't open security holes. Once both agents agree on the rules, they use `update_policy` to commit the changes. This automated peer-review process prevents bad configurations from hitting your production access control system.

Automated schema validation in AutoGen

The `add_schema` tool updates your resource schemas to ensure they match incoming authorization requests. A validation agent in AutoGen monitors these updates and compares them against existing schemas retrieved via `get_schema`. If a discrepancy is found, the agent triggers `disable_policy` on any affected rules to prevent invalid requests from causing runtime errors. The agents then discuss how to align the schema and policy definitions.

Real-time threat auditing with this AutoGen MCP Server

The `list_audit_logs` tool feeds real-time access decisions directly to an auditing agent. This agent scans for anomalous access patterns or repeated failures by checking logs against `get_metrics`. When a potential breach is detected, the auditing agent coordinates with an admin agent to run `check_resources` on the compromised account. They can dynamically restrict access by applying restrictive temporary rules.

Setup guide

Set up Cerbos (Access Control) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Cerbos (Access Control) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Cerbos (Access Control)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Cerbos (Access Control) data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Cerbos (Access Control)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Cerbos (Access Control) data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cerbos. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Cerbos (Access Control) MCP in AutoGen

One agent drafts the policy using `add_policy`, while a security agent reviews it. They debate the changes in a conversation loop until they reach consensus, then apply it.

Yes. Agents use `get_health` and `get_server_info` to monitor the Cerbos instance. If the system is unhealthy, a monitoring agent can notify your team or route requests elsewhere.

Use the `autogen-ext` package to connect to the MCP Server over HTTP or stdio. Pass the adapter-generated tools list directly into your AssistantAgent constructor.

The agents use the `plan_resources` tool to get the AST for filtering resources. They then translate this AST into database queries to enforce data isolation at the database level.

All evaluation payloads processed by this MCP Server run inside an ephemeral, zero-trust sandbox. Your access evaluation requests are processed in transit and never stored on Vinkius servers.

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