How to Use the Scoro MCP in AutoGen

Q: How do AutoGen agents access the Scoro MCP Server tools?

You register the tools using mcpservertools with your Vinkius HTTP URL. The McpToolAdapter automatically converts the Scoro schemas so your AutoGen AssistantAgent can invoke them during conversations.

Deploy AutoGen agent teams to debate Scoro project budgets and resource logs for consensus-driven decisions.

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Setup Scoro with AutoGen

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Debate Scoro Budgets with AutoGen Agents

This financial analysis tool lets multiple AutoGen agents deliberate over your Scoro business data. One agent can query `list_quotes` to analyze incoming revenue, while a second agent pulls `list_expenses` to audit outgoing costs. They debate the financial health of your projects before presenting a final recommendation. This multi-agent consensus prevents single-agent errors and flags budget risks before they impact your cash flow.

Coordinate Project Timelines via MCP Server

This timeline coordination tool keeps your projects on track by letting agents collaborate on schedules. An agent queries `list_tasks` to check project milestones, while another checks `list_calendar_events` to verify team availability. The agents negotiate timelines to resolve scheduling bottlenecks. Instead of a single model guessing the schedule, the agents reach a consensus based on actual Scoro workloads.

Audit Time Entries and Resource Allocation

This resource auditing tool optimizes your team's billable hours by letting agents audit logged time. Your AutoGen team uses `list_time_entries` to see where hours are spent and compares them against `list_users` to track individual workloads. A billing agent can flag unlogged time or overallocation, while a project agent suggests adjustments. This collaborative analysis ensures your resource tracking matches actual project progress.

Setup guide

Set up Scoro 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 Scoro 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="Scoro_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You register the tools using mcp_server_tools with your Vinkius HTTP URL. The McpToolAdapter automatically converts the Scoro schemas so your AutoGen AssistantAgent can invoke them during conversations.

Yes, you can set up a multi-agent chat where one agent queries `list_projects` and another reviews `list_time_entries`. They converse to reconcile differences between planned project hours and actual logged time.

Yes, the AutoGen MCP extension supports both stdio and Streamable HTTP transports. When hosted on Vinkius, you connect via the secure HTTP transport using a single endpoint token.

Yes, you can filter the list of tools passed to each AssistantAgent. For example, you can give your finance agent access to `list_invoices` while keeping your project agent restricted to `list_tasks`.

Your user lists and time entries are protected by end-to-end encryption during transport. Vinkius runs the Scoro MCP integration in isolated V8 sandboxes that do not log or store the payloads of your queries.

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