How to Use the Better Proposals MCP in AutoGen

Q: How do I hook up the Better Proposals MCP Server to AutoGen?

Install autogen-extmcp. Configure StreamableHttpServerParams with your Vinkius URL, extract the tools, and hand them to your agents.

Q: How do AutoGen agents know which Better Proposals template to use?

They query the API. An agent executes listtemplates, reviews the available options, and negotiates with the group on the best fit for the current client.

Give your AutoGen multi-agent debates access to Better Proposals data.

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Connect Better Proposals MCP to AutoGen

Create your Vinkius account to connect Better Proposals 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 Better Proposals with AutoGen

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Consensus-Driven Pitch Generation

This MCP Server exposes Better Proposals endpoints to your interacting AutoGen agents. A sales agent drafts a pitch, while a finance agent reviews the pricing using `get_proposal`. They debate the terms before finalizing anything. Once they reach an agreement, the system executes `create_proposal` and pushes the document live.

AutoGen MCP Server Integration

Fetch the tools using `mcp_server_tools` with your Vinkius HTTP endpoint. The `McpToolAdapter` handles all schema conversions for endpoints like `get_company` and `list_templates`. Pass the resulting list directly into your `AssistantAgent` constructor. Your agents instantly understand how to query contact records and parse analytics.

Multi-Agent Analytics Review

Evaluating pitch performance requires multiple perspectives. You assign one agent to pull metrics via `get_analytics` and another to cross-reference client data using `list_contacts`. The agents discuss why a specific document failed to convert. They analyze the read times, identify bottlenecks, and recommend changes for the next template update.

Setup guide

Set up Better Proposals 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 Better Proposals 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="Better Proposals_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Better Proposals 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 Better Proposals. 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

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Common questions about Better Proposals MCP in AutoGen

Install `autogen-ext[mcp]`. Configure `StreamableHttpServerParams` with your Vinkius URL, extract the tools, and hand them to your agents.

Yes. You provide the tool list to any agent in the conversation. A reviewer agent might use `get_proposal` while a creator agent uses `create_proposal`.

They query the API. An agent executes `list_templates`, reviews the available options, and negotiates with the group on the best fit for the current client.

The Vinkius marketplace provides a Streamable HTTP transport. You pass your single endpoint token in the configuration headers.

Vinkius strictly isolates your API traffic. The sandbox handling your `create_contact` and drafting requests is completely zero-trust and destroys itself after the operation finishes.

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