How to Use the Eden AI MCP in AutoGen

Q: Can AutoGen agents dynamically swap Eden AI providers?

Yes, during their conversation, AutoGen agents can query listaiproviders and agree on a new vendor. They use the updated Eden AI provider settings for subsequent tasks without human intervention.

Q: How does AutoGen handle budget limits with Eden AI?

An AutoGen agent can run getedenaimetadata to check your credit balance. If the balance is low, the agent can alert the group to switch to cheaper Eden AI models or pause expensive workflows.

Let your AutoGen agents debate and coordinate Eden AI workflows, provider pricing, and API usage budgets.

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Create your Vinkius account to connect Eden AI to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Eden AI with AutoGen

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Multi-agent cost negotiation using AutoGen and Eden AI

Set up an AutoGen debate between a budget agent and a performance agent using this Eden AI MCP Server. The AutoGen performance agent selects a premium model, while the budget agent calls `get_ai_feature_pricing` to challenge the Eden AI cost. They negotiate to find the cheapest Eden AI provider that meets the AutoGen performance threshold. They use `get_api_usage_statistics` to monitor the running total during their AutoGen conversation about Eden AI costs. If the current AutoGen session spend exceeds the limit, the budget agent forces a switch to a cheaper Eden AI model.

Collaborative provider auditing in AutoGen

When deploying a new feature, your AutoGen agents can audit available Eden AI vendors. One AutoGen agent calls `list_ai_providers` to get the raw list, while another runs `quick_ai_provider_audit` to analyze text analysis capabilities in Eden AI. The AutoGen agents debate the pros and cons of each Eden AI provider based on current health scores. Once they reach a consensus, the AutoGen agents output the optimal Eden AI provider configuration for your specific task.

Manage Eden AI workflows via AutoGen agent consensus

This MCP Server allows your AutoGen agents to manage your Eden AI automation pipelines collaboratively. A coordinator AutoGen agent calls `list_ai_workflows` to see what is running, while a QA agent reviews the setup using `get_workflow_configuration` from Eden AI. If the QA AutoGen agent detects an outdated Eden AI step, it alerts the coordinator. Together, the AutoGen agents verify the latest updates using `list_latest_ai_automations` before confirming the Eden AI workflow is safe to run.

Setup guide

Set up Eden AI 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 Eden AI 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="Eden AI_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Eden AI data")
    print(result.messages[-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Eden AI. 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 Eden AI MCP in AutoGen

You register the tools with the AutoGen AssistantAgent constructor using the MCP tool adapter. Both your budget and performance agents can call Eden AI tools like `get_ai_feature_pricing` during their debate.

Yes, during their conversation, AutoGen agents can query `list_ai_providers` and agree on a new vendor. They use the updated Eden AI provider settings for subsequent tasks without human intervention.

An AutoGen agent can run `get_eden_ai_metadata` to check your credit balance. If the balance is low, the agent can alert the group to switch to cheaper Eden AI models or pause expensive workflows.

Yes, AutoGen can connect to this Eden AI MCP server using either stdio or streamable HTTP. The MCP adapter automatically handles the schema conversion for all 10 tools.

All provider configurations and API usage statistics are kept within the memory space of your local AutoGen agents. The Vinkius zero-trust sandbox ensures your secrets are never stored or exposed to external LLM providers.

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