How to Use the Mela MCP in AutoGen

Debate project decisions by integrating Mela tools into your AutoGen multi-agent system.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Mela MCP to AutoGen

Create your Vinkius account to connect Mela 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.

GDPR Free for Subscribers

Setup Mela with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Negotiate site updates with AutoGen agents

Assign one agent to monitor `get_activity` status while another manages `post_message` notifications. They negotiate the timing and content of project updates to ensure nothing is missed. This approach prevents communication gaps. Your agents debate the best course of action before committing a change to the Mela platform.

Automate resource logging via AutoGen

Have your performance agent trigger `log_work_hours` while your security agent verifies the input against budget limits. They cross-check every entry before finalizing the record. This creates a system of checks and balances. You get the speed of automation with the caution of human-like deliberation.

Manage Mela activities with multiple agents

Use AutoGen to handle complex project changes that require consensus. Agents discuss the implications of using `update_activity_status` before executing the move. This is ideal for high-stakes projects. You avoid errors by forcing your agents to resolve conflicts before they touch your production site data.

Setup guide

Set up Mela 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 Mela 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="Mela_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Mela 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 Mela. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Mela now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Mela MCP in AutoGen

Install the AutoGen MCP extension and pass your server endpoint to the tool adapter. The system automatically converts Mela tool definitions into agent-callable functions.

They can. By setting up a conversation flow, you allow agents to challenge each other's proposed tool calls, ensuring `log_materials` data is accurate.

Vinkius manages the connection via an ephemeral sandbox. Your sensitive credentials never leave the secure environment, even when agents are debating data.

Yes, you can use either stdio or Streamable HTTP transports depending on your architecture. Both are supported for connecting Mela to your agent swarm.

Agents share the output of tool calls within their conversation history. This allows them to build on each other's findings without redundant API requests.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript