OpenCritic MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect OpenCritic through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="OpenCritic Assistant",
instructions=(
"You help users interact with OpenCritic. "
"You have access to 8 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from OpenCritic"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About OpenCritic MCP Server
Equip your AI agent with the most reliable video game intelligence available via OpenCritic. This unified server provides your agent with instant access to aggregate review scores, detailed critic snippets, and historical rankings for thousands of games. Your agent can instantly search for specific titles, audit recent review trends, and retrieve the Hall of Fame for any given year without you ever needing to browse a review site. Whether you are identifying the best games of the year or auditing individual critic opinions, your agent acts as a dedicated gaming analyst through natural conversation.
The OpenAI Agents SDK auto-discovers all 8 tools from OpenCritic through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries OpenCritic, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Game Discovery — Search for thousands of video games by title and retrieve their OpenCritic rating and tier.
- Review Auditing — Fetch detailed snippets and scores from individual critics and publications for any game.
- Market Trends — Retrieve lists of upcoming releases and currently popular/trending games on the platform.
- Historical Rankings — Access the 'Hall of Fame' to identify the top-rated games for a specific year.
- Critic Intelligence — List and inspect recognized critics and publications to understand the source of reviews.
The OpenCritic MCP Server exposes 8 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect OpenCritic to OpenAI Agents SDK via MCP
Follow these steps to integrate the OpenCritic MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 8 tools from OpenCritic
Why Use OpenAI Agents SDK with the OpenCritic MCP Server
OpenAI Agents SDK provides unique advantages when paired with OpenCritic through the Model Context Protocol.
Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
OpenCritic + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the OpenCritic MCP Server delivers measurable value.
Automated workflows: build agents that query OpenCritic, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries OpenCritic, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through OpenCritic tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query OpenCritic to resolve tickets, look up records, and update statuses without human intervention
OpenCritic MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect OpenCritic to OpenAI Agents SDK via MCP:
get_game_details
Get game details
get_game_reviews
Get game reviews
get_hall_of_fame
Get Hall of Fame games
get_popular_games
Get popular games
get_recent_reviews
Get recent reviews
get_upcoming_games
Get upcoming games
list_critics
List critics
search_games
Search for video games
Example Prompts for OpenCritic in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with OpenCritic immediately.
"What is the OpenCritic score for 'Elden Ring'?"
"List the top games from 2023."
"Show me upcoming games on OpenCritic."
Troubleshooting OpenCritic MCP Server with OpenAI Agents SDK
Common issues when connecting OpenCritic to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
OpenCritic + OpenAI Agents SDK FAQ
Common questions about integrating OpenCritic MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect OpenCritic with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect OpenCritic to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.