How to Use the Fee Navigator MCP in AutoGen

Use AutoGen to let agents debate fee analysis and audit results, ensuring your proposal strategy is vetted by multiple perspectives.

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Connect Fee Navigator MCP to AutoGen

Create your Vinkius account to connect Fee Navigator 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 Fee Navigator with AutoGen

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Debate merchant fees with AutoGen

Assign one agent to `analyze_statement` and another to check `get_industry_stats`. The agents compare the results and negotiate the best proposal terms. This forces a consensus before any document is finalized. You get a better result because the agents challenge each other's assumptions about the merchant's data.

Manage audit tasks with this MCP Server

Let a security agent call `get_audit` while an operations agent reviews `list_proposals`. They resolve discrepancies in the audit data before presenting the final report to you. This creates a system of checks and balances. You define the agents, and the server provides the tools they need to perform their roles.

Scale analysis with AutoGen multi-agent flows

Deploy a team of agents to process high volumes of merchant data. They use `list_merchants` to divide the workload and `get_me` to verify their own access levels. This keeps your operations moving fast. Each agent handles a specific part of the financial audit, and the MCP server ensures they all have the data they need.

Setup guide

Set up Fee Navigator 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 Fee Navigator 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="Fee Navigator_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Use the MCP server tools adapter to import all 12 tools into your agent definition. This allows your assistant agents to call the API directly during their conversation.

Yes. You can build a conversation where one agent proposes savings based on `get_proposal` and another verifies the math using `get_industry_stats`.

Every request is authenticated via your endpoint token. The server enforces strict access control, ensuring that agents only access the merchant information authorized for your account.

Yes. You can connect to the server using either transport method. The MCP tool adapter handles the schema translation, making the tools available to your agents immediately.

Agents receive standard error responses from the API. You can instruct your agents to attempt a retry or pivot to a different tool if an audit or analysis fails.

Use it with your favorite AI tools

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