How to Install Sentry MCP in OpenAI Agents SDK
Official Sentry integration — bring live error context, stack traces, and performance data into your AI
What Sentry MCP does
The official Sentry MCP server pulls live error data directly into your AI agent. Instead of screenshotting stack traces and pasting them into chat, point Claude at a Sentry issue — it gets full context, correlates with releases, and suggests fixes. Features: - Query issues by project, environment, and time range - Get full stack traces with local variables - Access performance transaction data and bottlenecks - Correlate errors with recent deployments and releases - Search events by user, URL, tag, or error type - Manage issue status (resolve, ignore, merge) - Access release health metrics - Set up alert rules and notification policies The typical workflow: 1. Claude sees an error in your code 2. Claude queries Sentry for matching recent issues 3. Pulls the full stack trace, breadcrumbs, and affected users 4. Suggests a fix with full context — no manual copy-paste Built and maintained by Sentry. OAuth-based — no stored API keys.
Installation steps
- 1Install: pip install openai-agents
- 2Copy the snippet below into your agent code
- 3Replace placeholder env values with your real keys
- 4Pass mcp_servers=[mcp_server] to your Agent()
Python snippet
from agents import Agent
from agents.mcp import MCPServerStdio
mcp_server = MCPServerStdio(
command="npx",
args=["-y", "@sentry/mcp-server"],
env={
"SENTRY_AUTH_TOKEN": "sntrys_...",
"SENTRY_ORG": "your-org",
},
)
agent = Agent(
name="My Agent",
model="gpt-4o",
mcp_servers=[mcp_server],
)Install in other clients
For maintainers
If you maintain Sentry MCP, add this badge to your README to show it's verified on CuratedMCP:
[](https://curatedmcp.com/marketplace/sentry-mcp)