How to Use the Dalil AI MCP in AutoGen

Q: How do I register Dalil AI MCP tools with AutoGen?

Use the mcpservertools helper with your Vinkius endpoint URL. This maps the Arabic prospecting capabilities directly to your AssistantAgent constructor.

Q: Does this support multi-agent parallel execution?

Yes, separate agents can query listcontacts and listcampaigns simultaneously. The underlying Vinkius infrastructure handles the concurrent requests without bottlenecks.

Enable multi-agent debate over Middle Eastern prospecting strategies using AutoGen.

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Connect Dalil AI MCP to AutoGen

Create your Vinkius account to connect Dalil AI 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 Dalil AI with AutoGen

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Run multi-agent debates on Arabic lead quality

This MCP Server exposes `get_contact_signals` to let your AutoGen agents debate whether a Middle Eastern lead is ready for outreach. One agent analyzes the raw buying signals while another checks historical response rates to reach a consensus. This collaborative filtering ensures you only target high-value accounts. The agents argue the merits of each lead in real-time, preventing wasted effort on cold accounts.

Validate localized LinkedIn copy before sending

The `send_linkedin_message` tool is guarded by an AutoGen critique loop where a translation agent reviews the Arabic text for cultural nuance. A separate compliance agent checks the message against regional business etiquette. Only when both agents agree on the phrasing does the system execute the actual message dispatch. This workflow protects your brand reputation in sensitive Middle Eastern markets.

Manage multi-agent campaigns via AutoGen MCP Server

Your coordinator agent executes `list_campaigns` to assess which outreach sequences are currently running in the region. It then assigns different sub-tasks to specialist agents based on active campaign performance. A writer agent drafts updates while an analyst agent monitors target responses using `list_contacts`. This division of labor keeps your regional prospecting organized and highly targeted.

Setup guide

Set up Dalil AI 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 Dalil AI 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="Dalil AI_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Your supervisor agent registers the tools and delegates execution of `list_companies` to a specialized search agent. The resulting Middle Eastern corporate data is then shared in the group chat for other agents to analyze.

Yes, you can configure a critic agent to inspect the payload destined for `send_linkedin_message`. If the Arabic phrasing fails tone checks, the critic agent halts the conversation before the tool runs.

Use the `mcp_server_tools` helper with your Vinkius endpoint URL. This maps the Arabic prospecting capabilities directly to your AssistantAgent constructor.

Yes, separate agents can query `list_contacts` and `list_campaigns` simultaneously. The underlying Vinkius infrastructure handles the concurrent requests without bottlenecks.

Every tool execution runs in a sandboxed V8 isolate that is torn down immediately after use. Your sensitive regional lead lists and message contents are never stored on host servers.

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