How to Use the MACD & RSI Oscillator Engine MCP in AutoGen

Q: How do I integrate the MACD & RSI Oscillator Engine into AutoGen?

Install the autogen-extmcp package and use the mcpservertools utility. It maps the tool schema automatically so your AssistantAgent can use it immediately.

Let your AutoGen agents debate market signals using the MACD & RSI Oscillator Engine.

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Connect MACD & RSI Oscillator Engine MCP to AutoGen

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Setup MACD & RSI Oscillator Engine with AutoGen

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Perplexity

Consensus-driven technical analysis

Your AutoGen agents can call `calculate_macd_rsi` to get the raw signals they need to debate a trade. One agent might focus on the RSI, while another scrutinizes the MACD histogram. They challenge each other's interpretation of these indicators to reach a consensus. This prevents impulsive decisions based on a single, isolated data point.

Automated tool negotiation

The `calculate_macd_rsi` tool fits perfectly into the AutoGen assistant agent structure. Agents negotiate which parameters to pass based on the current market volatility. This makes your system dynamic. Instead of static settings, your agents adjust the period parameters in real-time as they discuss the market conditions.

Debate-ready indicator math

The math engine is fast enough to support multiple agents requesting data simultaneously. It handles the heavy lifting so your agents can focus on the logic of the trade. Your agents compare the output against their own internal reasoning models. This process creates a robust decision loop where the indicator data acts as the common ground for all participants.

Setup guide

Set up MACD & RSI Oscillator Engine 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 MACD & RSI Oscillator Engine 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="MACD & RSI Oscillator Engine_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent MACD & RSI Oscillator Engine data")
print(result.messages[-1].content)

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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="MACD & RSI Oscillator Engine_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent MACD & RSI Oscillator Engine data")
    print(result.messages[-1].content)

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Common questions about MACD & RSI Oscillator Engine MCP in AutoGen

Yes. Agents can pass the results of the tool to each other during their conversation to refine their analysis before making a final decision.

Install the autogen-ext[mcp] package and use the mcp_server_tools utility. It maps the tool schema automatically so your AssistantAgent can use it immediately.

Yes, they can discuss the values returned by the tool to reach a consensus, ensuring that both RSI and MACD signals are accounted for.

It executes in under 5ms, which is plenty for multi-agent conversations. It keeps your debate loop responsive even during rapid price changes.

All calculations occur in a sandboxed local environment. Your price data and the resulting indicator signals remain within your controlled AutoGen execution space.

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