How to Use the Pics.io MCP in AutoGen

Q: How can AutoGen agents search for Pics.io assets?

Agents share access to the searchassets tool. They debate which query parameters yield the best results before settling on a final list.

Q: Can I use Pics.io to track agent decisions?

Yes. You can have an agent use addcomment to log the outcome of a debate directly on the relevant asset.

Coordinate multi-agent debates in AutoGen to manage Pics.io assets with consensus-driven decision making for your creative team.

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…and any MCP-compatible client

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Connect Pics.io MCP to AutoGen

Create your Vinkius account to connect Pics.io to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Pics.io with AutoGen

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Multi-agent asset management in AutoGen

Deploy agents that debate the best way to use `update_asset` and `add_comment`. One agent proposes a metadata change while another verifies it against your naming convention. They negotiate until they reach a decision. It prevents errors that happen when a single agent operates without oversight.

Collaborative collection planning

Use `create_collection` and `delete_collection` in a multi-agent loop. The agents discuss if a new folder is needed before executing the command. This keeps your library clean. You define the rules, and the agents enforce them through their debate.

Debate-based asset discovery

Agents use `search_assets` to find files for a project. They challenge each other's search results to ensure the most relevant files are picked. You get better results because the agents check each other's work. It’s a robust way to handle complex asset requests.

Setup guide

Set up Pics.io 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 Pics.io 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="Pics.io_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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