How to Use the Messari MCP in OpenAI Agents SDK

Q: How do I connect the Messari MCP Server to my OpenAI Agents SDK project?

Install the SDK via pip and use the MCPServerStreamableHttp class with your Vinkius endpoint. Pass the server instance directly to your Agent constructor inside an async context manager. The SDK automatically discovers all ten tools.

Q: Does the Messari integration with OpenAI Agents SDK support caching?

Yes, you can set cacheToolsList=True during initialization to improve performance. This prevents the SDK from querying the Vinkius endpoint for the tool schema on every single turn, reducing latency.

Q: Can I coordinate multiple agents to analyze data from this server?

You can. Use one specialized agent to pull news via getcryptonews, then hand off the analysis to a quantitative agent that checks prices with getassetmarketdata.

Feed real-time token metrics and governance events directly into your OpenAI Agents SDK pipelines with zero manual config.

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Connect Messari MCP to OpenAI Agents SDK

Create your Vinkius account to connect Messari 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 Messari with OpenAI Agents SDK

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Feed live market metrics to OpenAI Agents SDK.

The `get_asset_metrics` tool pulls live quantitative data directly into your agent runtime. Your agent uses this data to evaluate market shifts on the fly without relying on stale, hardcoded numbers. By using `get_asset_market_data` alongside this MCP Server, your system monitors price action across various trading pairs. The OpenAI dashboard traces these calls automatically, giving you a clear audit trail of every data point your agent uses to make decisions.

Automate asset profiling and search.

The `search_assets` tool lets your agent find specific tokens based on raw search queries. Once found, the agent calls `get_asset_profile` to pull down the project details, founding team, and underlying technology. This setup lets you build specialized research agents that pass structured profiles to execution agents. The Messari MCP Server lets you build these specialized flows without writing custom parsing code because the tools handle the raw data delivery directly.

Track governance and news feeds.

The `get_crypto_news` tool delivers a live stream of market-moving updates directly to your LLM context window. Your agent can read these headlines to detect sudden sentiment shifts or regulatory changes. To monitor protocol changes, the agent invokes `list_governance_events` to keep tabs on DAO proposals. Combining these tools lets your system flag critical events before they impact your portfolio.

Setup guide

Set up Messari 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 Messari tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Messari 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="Messari Agent",
            instructions="You have access to Messari 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 Messari MCP in OpenAI Agents SDK

Install the SDK via pip and use the `MCPServerStreamableHttp` class with your Vinkius endpoint. Pass the server instance directly to your Agent constructor inside an async context manager. The SDK automatically discovers all ten tools.

Yes, you can control tool access using the built-in guardrails in the SDK. You define validation logic that checks the tool name before execution, preventing your agent from calling tools like `list_crypto_markets` if you only want it reading news.

Yes, you can set `cacheToolsList=True` during initialization to improve performance. This prevents the SDK from querying the Vinkius endpoint for the tool schema on every single turn, reducing latency.

You can. Use one specialized agent to pull news via `get_crypto_news`, then hand off the analysis to a quantitative agent that checks prices with `get_asset_market_data`.

The server only processes read-only crypto market data, news feeds, and asset profiles. Vinkius handles the underlying authentication tokens in an isolated sandbox, meaning your raw API keys are never exposed to the agent or the LLM provider.

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