How to Use the NMKR Cardano MCP in AutoGen
Deploy AutoGen multi-agent squads to debate Cardano NFT configurations and monitor NMKR payout structures autonomously.
Works with every AI agent you already use
…and any MCP-compatible client
Connect NMKR Cardano MCP to AutoGen
Create your Vinkius account to connect NMKR Cardano 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 consensus for Cardano mints
A finance agent checks `get_mint_coupon_balance` and `get_project_discounts` to calculate absolute costs while a compliance agent reviews metadata. You assign different roles to AutoGen assistants to divide the workload. They debate the deployment. If `validate_nft_metadata` fails, the compliance agent blocks the mint. The finance agent then proposes a cheaper batch size based on the active coupons. They negotiate until both conditions are met.
Audit payout structures with this MCP Server
You give an auditor agent access to `list_split_addresses` and `list_vesting_addresses` to pull the raw configuration from the MCP Server. Revenue splits require strict oversight. The agent acts as an independent reviewer. A second agent acts as the project manager, querying `list_subcustomers`. The two agents cross-reference the sub-customer accounts against the vesting schedules. If an address is missing, they flag the discrepancy in the terminal.
Monitor project metrics autonomously
Set up a watcher agent that periodically calls `get_project_counts` to track total minted versus remaining supply. The agent operates without human input. It polls the NMKR endpoint at set intervals. When the count hits a specific threshold, it alerts a reporting agent. That agent uses `list_project_nfts` to grab the latest minted tokens. It formats a summary and outputs the final consensus to your team.
Set up NMKR Cardano 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 NMKR Cardano 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="NMKR Cardano_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent NMKR Cardano 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="NMKR Cardano_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent NMKR Cardano 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 NMKR. 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 NMKR Cardano MCP in AutoGen
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