How to Use the Fibery MCP in AutoGen

Q: How do I register Fibery tools in AutoGen?

Install autogen-extmcp via pip. Use mcpservertools with StreamableHttpServerParams pointing to your Vinkius endpoint, then pass the returned tools list to your AssistantAgent constructor.

Q: Can multiple AutoGen agents use Fibery tools simultaneously?

Yes, multiple agents can access tools like queryentities or addcomment within the same conversational session. The McpToolAdapter manages tool execution and schema compliance for each agent automatically.

Run multi-agent debates that manage your Fibery workspace and coordinate tasks using AutoGen.

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Connect Fibery MCP to AutoGen

Create your Vinkius account to connect Fibery 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 Fibery with AutoGen

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Multi-agent triage with AutoGen and Fibery

This system uses `query_entities` and `list_users` to fuel collaborative team discussions between autonomous agents. A triage agent can pull new tickets, while a resource agent checks team availability. They discuss who is best suited for the task before making any changes to the workspace. Instead of a single agent making blind updates, AutoGen's conversational loop forces agents to cross-verify their plans. One agent drafts an update, and another checks it against the database schema retrieved by `get_schema`. This debate ensures that your MCP agent only pushes valid, high-quality updates to your workspace.

Collaborative comment moderation and updates

Your agents call `add_comment` and `update_entity` after reaching consensus on a task's progress. For example, a quality assurance agent might flag a bug as resolved, prompting the project manager agent to write a summary comment and close the ticket. You register these tools with your `AssistantAgent` using the `mcp_server_tools` helper. The `McpToolAdapter` handles the schema conversion automatically, allowing your agents to focus on the conversation rather than API formatting details.

Automated workspace cleanup and archiving

The cleanup loop uses `delete_entity` and `search_entities` to safely remove duplicate records after a thorough agent review. A supervisor agent identifies potential duplicates and asks a validator agent to check if the records are safe to delete. This workflow is powered by the HTTP transport layer using `StreamableHttpServerParams` pointing to Vinkius. The secure, isolated environment ensures that destructive actions like entity deletion are only executed after multiple agents have verified the necessity in their chat logs.

Setup guide

Set up Fibery 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 Fibery 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="Fibery_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Install `autogen-ext[mcp]` via pip. Use `mcp_server_tools` with `StreamableHttpServerParams` pointing to your Vinkius endpoint, then pass the returned tools list to your `AssistantAgent` constructor.

Yes, multiple agents can access tools like `query_entities` or `add_comment` within the same conversational session. The `McpToolAdapter` manages tool execution and schema compliance for each agent automatically.

You can set up a multi-agent consensus loop where a supervisor agent must approve any `delete_entity` call proposed by a worker agent. This conversational gatekeeping keeps your workspace safe from accidental deletions.

It supports both stdio and Streamable HTTP transports. When hosted on Vinkius, you will use the Streamable HTTP transport configured with your secure workspace token.

Your workspace schema and entity details are processed in an isolated, ephemeral V8 sandbox. Vinkius secures your API token and handles authentication, ensuring your database layouts are never exposed to external parties.

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