How to Use the Kelkoo MCP in AutoGen
Let AutoGen agents debate and find the best Kelkoo merchant offers and coupons through collaborative reasoning.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Kelkoo MCP to AutoGen
Create your Vinkius account to connect Kelkoo 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.
Multi-agent price negotiation using AutoGen
Heads up: you can set up a buyer agent and a discount agent that negotiate using `search_offers` and `search_coupons`. The buyer agent locates the base prices while the discount agent searches for matching coupons to lower the total cost. By using `get_offer_details`, the agents can compare shipping costs and merchant ratings to decide which offer is actually the best deal, rather than just picking the lowest sticker price.
Let agents debate merchant reliability
Configure an AutoGen performance analyst agent that calls `get_reporting_summary` and `list_merchants` to analyze merchant performance. This analyst can challenge a procurement agent's choices if a merchant has poor conversion or reporting history. This multi-agent setup ensures that your system doesn't blindly recommend offers. The agents use the MCP Server tools to cross-reference data before presenting the final verified options to the user.
Automated catalog mapping and taxonomy validation
Deploy an AutoGen coordinator agent to run `list_countries` and delegate specific regions to sub-agents. These sub-agents then pull regional structures using `list_categories` and `get_category_tree` to map out local catalogs. The agents can compile their findings and debate the best way to categorize products across different borders, resolving taxonomical conflicts before outputting the final structured data.
Set up Kelkoo 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Kelkoo tools and returns structured results.
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="Kelkoo_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Kelkoo data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Kelkoo_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Kelkoo data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kelkoo. 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 Kelkoo MCP in AutoGen
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