How to Use the TrueFoundry MCP in AutoGen

Q: What happens if AutoGen needs to verify an MCP Server's existence?

It checks the registry using truefoundrylistmcpservers. If the tool isn't listed, the agents know they can't proceed with that capability, preventing a false consensus.

Q: Does TrueFoundry help AutoGen manage resource allocation?

Yes. Agents can use truefoundrydeploymcpserver to provision the necessary backend container process needed for their current task, ensuring they have the resources before starting the deliberation.

Q: Can TrueFoundry help AutoGen evaluate system readiness?

Absolutely. Agents can call truefoundrygetdeploymentstatus to gather live metric data. This objective measurement is crucial for agents to decide if a planned action is feasible.

Q: What data type does TrueFoundry expose regarding deployment status?

The truefoundrygetdeploymentstatus tool emits detailed metric states on the orchestration matrix bounds, giving you hard data on container health and resource allocation.

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Setup TrueFoundry with AutoGen

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Perplexity

TrueFoundry for AutoGen: Running Gateway Chat Debates.

When multiple agents disagree on the best path, they need a source of truth. Use `truefoundry_run_gateway_chat` to push complex queries through TrueFoundry's gateway. Agents can then debate which model output is most authoritative for their final decision.

TrueFoundry for AutoGen: System State Negotiation.

For agents to reach consensus, they must agree on the system state. You run `truefoundry_get_deployment_status` and `truefoundry_list_deployments`. Agents can challenge each other's assumptions based on whether a required service is actually running or if its metrics are optimal.

TrueFoundry for AutoGen: Defining the Operational Space.

Before agents start debating, they need boundaries. Use `truefoundry_list_mcp_servers` to provide a definitive list of all available MCP Tools. This confines the negotiation space, making sure agents aren't arguing over non-existent capabilities.

Setup guide

Set up TrueFoundry 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 TrueFoundry 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="TrueFoundry_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent TrueFoundry 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="TrueFoundry_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent TrueFoundry 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 TrueFoundry. 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 TrueFoundry MCP in AutoGen

AutoGen can pass conflicting results from different sources—like two separate calls to `truefoundry_run_gateway_chat`—to the agents. The agents then discuss these competing outputs until a consensus is reached.

It checks the registry using `truefoundry_list_mcp_servers`. If the tool isn't listed, the agents know they can't proceed with that capability, preventing a false consensus.

Yes. Agents can use `truefoundry_deploy_mcp_server` to provision the necessary backend container process needed for their current task, ensuring they have the resources before starting the deliberation.

Absolutely. Agents can call `truefoundry_get_deployment_status` to gather live metric data. This objective measurement is crucial for agents to decide if a planned action is feasible.

The `truefoundry_get_deployment_status` tool emits detailed metric states on the orchestration matrix bounds, giving you hard data on container health and resource allocation.

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