How to Use the Gandi.net (Domain Registration & Hosting API) MCP in AutoGen

Q: Can I have a human approve a DNS change proposed by an agent?

Absolutely. You can set up a UserProxyAgent that requires human input to approve critical function calls. The agent conversation will pause until you type 'yes' to confirm the updatednsrecord call.

Let your AutoGen agents debate and manage Gandi.net domains. Build teams of agents for secure, collaborative DNS operations.

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Connect Gandi.net (Domain Registration & Hosting API) MCP to AutoGen

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Setup Gandi.net (Domain Registration & Hosting API) with AutoGen

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Let agents debate DNS changes before applying.

Create a team of agents to handle DNS updates. One agent proposes a change using `update_dns_record`, while a 'SecurityAgent' reviews it, maybe by running `list_dns_records` to check for conflicts. The change only gets applied after the agents reach a consensus. This prevents careless mistakes and builds a review process directly into your automation, all orchestrated by AutoGen's conversational framework.

Team-based domain and mailbox setup.

Spin up a 'ProvisionerAgent' that uses `check_domain` to find available domains. It can then propose a domain to a 'FinanceAgent' that checks a budget, and a 'ProductAgent' that confirms the name fits the brand. Once they agree, the ProvisionerAgent can execute `create_mailbox` and `create_dns_record` to set everything up. This MCP Server gives each agent the specific tools they need to do their part.

Automated incident response with AutoGen.

A monitoring alert can trigger an AutoGen workflow. A 'TriageAgent' uses `get_domain` and `list_dns_records` to investigate a reported domain issue. It presents its findings to a 'NetworkAgent'. The NetworkAgent can then propose a fix, like using `update_dns_record` to reroute traffic. A human-in-the-loop can approve the final action. It's a command center staffed by specialized agents.

Setup guide

Set up Gandi.net (Domain Registration & Hosting API) 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 Gandi.net (Domain Registration & Hosting API) 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="Gandi.net (Domain Registration & Hosting API)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Gandi.net (Domain Registration & Hosting API) data")
print(result.messages[-1].content)

Get your connection token →

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="Gandi.net (Domain Registration & Hosting API)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Gandi.net (Domain Registration & Hosting API) 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 Gandi.net. 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 Gandi.net (Domain Registration & Hosting API) MCP in AutoGen

When you load the tools from the MCP server, you get a dictionary. You can then register different subsets of those tools with each agent, giving them only the functions they need to do their job.

Yes, that's a core pattern. One agent can perform an action with `create_dns_record`, and a second 'AuditorAgent' can then use `list_dns_records` to confirm the change was made correctly before the group chat concludes.

The tools appear as functions the agents can call. An agent decides to call a tool, its output is posted back into the chat as a message, and then other agents (or the same one) can react to that new information.

Absolutely. You can set up a `UserProxyAgent` that requires human input to approve critical function calls. The agent conversation will pause until you type 'yes' to confirm the `update_dns_record` call.

Your agents only interact with the Gandi.net data they're programmed to, like domain availability via `check_domain` or organization lists. The Vinkius MCP server architecture means your Gandi.net credentials are never exposed to the agents or the chat history.

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