How to Use the Nansen (Blockchain Analytics) MCP in OpenAI Agents SDK

Q: How do I connect Nansen (Blockchain Analytics) to my OpenAI Agents SDK project?

You instantiate an MCPServerStreamableHttp object with your endpoint. Add this to your Agent constructor's mcpservers list to let the agent auto-discover all 48 tools.

Q: Can I cache tools for Nansen (Blockchain Analytics) in OpenAI Agents SDK?

Absolutely. Set cacheToolsList=True in your configuration to improve performance. This keeps your agent responsive during high-volatility events where latency matters.

Q: Is it possible to trace Nansen (Blockchain Analytics) calls in OpenAI Agents SDK?

The SDK handles full tracing automatically. Every call to smartmoneyholdings appears in your OpenAI dashboard logs, making debugging straightforward.

Plug Nansen (Blockchain Analytics) into your OpenAI Agents SDK production pipeline for real-time institutional on-chain data.

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Connect Nansen (Blockchain Analytics) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Nansen (Blockchain Analytics) to OpenAI Agents SDK 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 Nansen (Blockchain Analytics) with OpenAI Agents SDK

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Automated Smart Money tracking with OpenAI Agents SDK

Feed `smart_money_netflow` and `smart_money_dex_trades` directly into your agents to capture institutional movement. Your code handles the logic while the agent interprets the signal. Stop guessing where the capital flows. Use `tgm_flow_intelligence` to build automated triggers that detect institutional accumulation before the retail market reacts.

Real-time wallet profiling for your OpenAI agent

Call `profiler_pnl_summary` to verify if a wallet address is actually profitable or just lucky. This keeps your agent focused on alpha-generating participants. Cross-reference activity with `profiler_related_wallets` to find hidden clusters. You get granular, typed data back in your pipeline without manual lookups.

Production-ready token market intelligence

Use `tgm_token_information` to pull spot stats into your agent's decision loop. It provides the metadata needed to validate trades against real volume. Keep your agent's context accurate with `tgm_token_ohlcv`. It feeds raw price history directly into your model, ensuring the data driving your decisions is current.

Setup guide

Set up Nansen (Blockchain Analytics) MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Nansen (Blockchain Analytics) tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Nansen (Blockchain Analytics) tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Nansen (Blockchain Analytics) tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Nansen (Blockchain Analytics) Agent",
            instructions="You have access to Nansen (Blockchain Analytics) tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Nansen (Blockchain Analytics) MCP in OpenAI Agents SDK

You instantiate an `MCPServerStreamableHttp` object with your endpoint. Add this to your `Agent` constructor's `mcp_servers` list to let the agent auto-discover all 48 tools.

Yes. Since your tools are mapped as native functions, the SDK validates the schema before execution. Any unexpected data from `profiler_transactions` gets caught by your existing safety layers.

Absolutely. Set `cacheToolsList=True` in your configuration to improve performance. This keeps your agent responsive during high-volatility events where latency matters.

The SDK handles full tracing automatically. Every call to `smart_money_holdings` appears in your OpenAI dashboard logs, making debugging straightforward.

Your agent only interacts with public on-chain data like token transfers and wallet balances. No private keys or sensitive user credentials ever leave your environment.

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