How to Use the Galxe MCP in OpenAI Agents SDK

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Connect Galxe MCP to OpenAI Agents SDK

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

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Automate Quest Eligibility Checks

You don't want your community managers spending three hours a day manually verifying if users completed Galxe tasks. Connect this MCP Server to your OpenAI Agents SDK setup, and your agent handles the verification automatically. The agent uses `check_quest_eligibility` and `check_credential_eligibility` to instantly confirm user status. If someone asks why they didn't get their points, the agent pulls the exact requirement mismatch and explains it, fully backed by OpenAI's built-in guardrails to ensure it doesn't hallucinate a passing grade.

Track Web3 Loyalty Leaderboards

Stop pulling CSVs to figure out who your top contributors are. Your agent can read live rankings directly from your Galxe space and push that data into your internal dashboards or Discord channels. By calling `get_space_leaderboard` and `get_starboard_leaderboard`, the agent tracks both general loyalty points and Twitter influence. You can even set up agent handoffs where one agent monitors the leaderboard and another drafts personalized DMs to the top ten users.

Manage API Credentials Programmatically

Managing allowlists usually means updating static files or clicking through a web interface. We built this integration so your agent can update eligible users on the fly based on custom business logic. When a user passes your custom off-chain verification, the agent fires `mutate_credential_items` to add them to the Galxe credential list. Everything gets logged and traced in your OpenAI dashboard, so you always know exactly which agent modified the allowlist.

Setup guide

Set up Galxe 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 Galxe tools at runtime.
3

Create your Agent

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

Run the agent

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

Initialize MCPServerStreamableHttp with your endpoint URL. Pass it into your agent constructor using mcp_servers=[server]. Tools auto-discover immediately.

Yes. The agent uses the mutate tool to add or remove users from API credentials. You can wrap this in OpenAI guardrails to require human approval before execution.

It does. Set cacheToolsList=True when configuring the MCP Server. This stops the agent from refetching the tool definitions on every single run.

Webhooks only notify you when something happens. An agent can read a quest via get_quest, check a user's eligibility, and dynamically update a credential list based on a natural language prompt.

It accesses wallet addresses, social handles, and quest participation records. Your OpenAI tracing logs will capture these parameters during tool execution, so ensure your data retention policies align with handling Web3 identity markers.

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