How to Use the Ayanza MCP in AutoGen

Connect AutoGen agents to coordinate Ayanza tasks, projects, and wikis through multi-agent debate and consensus.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Ayanza MCP to AutoGen

Create your Vinkius account to connect Ayanza 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 Ayanza with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-Agent Workspace Collaboration

Your AutoGen team uses `list_tasks` and `list_users` to analyze team workload and debate assignments. A manager agent proposes an owner, while an analyst agent checks current task loads to reach a consensus. Once the agents agree, they execute `update_task` to finalize the assignment. This collaborative loop ensures that project updates are thoroughly vetted before changing anything in your workspace.

Automated Quality Gates with the Ayanza MCP Server

This integration lets your AutoGen agents audit workspace documentation using `list_wiki_pages`. One agent drafts a new project spec, while a reviewer agent checks it against existing wiki guidelines. The agents debate the gaps, refine the text, and then call `create_task` to track the implementation. You get a self-correcting workflow that maintains high documentation standards without human oversight.

Dynamic Task Deletion Safety

The agent team runs `delete_task` only after a multi-agent validation process. A cleanup agent identifies obsolete tasks, while a safety agent verifies the task status using `get_task` to prevent accidental loss. This debate prevents destructive actions from running unchecked. The conversation logs show the exact reasoning path before the final tool execution occurs.

Setup guide

Set up Ayanza 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 Ayanza 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="Ayanza_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You register the tools with your AssistantAgent using the MCP tool adapter. This gives your agents immediate access to commands like `list_projects` and `create_task`.

Yes, you can distribute tools across different agents. For instance, your researcher agent uses `list_wiki_pages` while your coordinator agent handles `create_task`.

The AutoGen MCP extension automatically handles schema conversion. Your agents can call `get_project` or `list_users` using native AutoGen function-calling structures.

You can configure the server to target specific workspaces. Your agents use `get_me` to verify their active environment before initiating debates on tasks.

Your task details and wiki pages are processed in an ephemeral V8 sandbox. Vinkius ensures that the text analyzed by your agents is never cached or exposed to outside networks.

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