Sentry MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Sentry through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Sentry, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
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 Sentry MCP Server
Equip your favorite LLM interface with direct, real-time investigative access over your application's Sentry operational environments. Skip the grueling task of combing through the rigid crash dashboard visually. Now, your AI can pull up the latest software exceptions directly into Cursor or an MCP-enabled chat window, read the contextual stack trace natively, and even close out resolved bugs.
The Vercel AI SDK gives every Sentry tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Live Crash Monitoring — Query the
list_issuesfunctionality at any time to instantly see which endpoints or functions are currently malfunctioning and throwing fatal alerts - Deep Error Inspection — Feed an
issue_idto the agent viaget_issue_details. The LLM will devour the entire stack trace, evaluate the environmental metadata, and suggest precisely which lines of code need attention - Project & Organization Forensics — Interrogate the AI regarding internal structures (
list_users,list_teams) and easily scan separate software branches or repositories (list_projects) configured in your Sentry silo - Alert Triage (Mutable) — Dictate the agent to close resolved items (
resolve_issue), marking the exception safely as handled without having to load the web interface
The Sentry MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI 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 Sentry to Vercel AI SDK via MCP
Follow these steps to integrate the Sentry MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from Sentry and passes them to the LLM
Why Use Vercel AI SDK with the Sentry MCP Server
Vercel AI SDK provides unique advantages when paired with Sentry through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same Sentry integration everywhere
Built-in streaming UI primitives let you display Sentry tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Sentry + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Sentry MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Sentry in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Sentry tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Sentry capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Sentry through natural language queries
Sentry MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Sentry to Vercel AI SDK via MCP:
delete_issue
This action is irreversible. Permanently deletes an issue
get_event_details
Retrieves details for a specific event
get_issue_details
Retrieves details for a specific issue
list_events
Lists recent events for a project
list_issues
Lists all issues (errors) in a project
list_organization_teams
Lists all teams in an organization
list_organization_users
Lists all users in an organization
list_organizations
Lists all Sentry organizations
list_projects
Lists all projects in an organization
resolve_issue
This is a reversible side-effect. Resolves an issue in Sentry
Example Prompts for Sentry in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Sentry immediately.
"Enumerate the most recently flared active open errors across the 'frontend-ui' project portal in Sentry."
"Fetch all pertinent internal parameters regarding issue id 6B3VX4921."
"I've deployed a patch fixing the deadlock in db.ts. Mutate this specific issue globally to 'resolved'."
Troubleshooting Sentry MCP Server with Vercel AI SDK
Common issues when connecting Sentry to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpSentry + Vercel AI SDK FAQ
Common questions about integrating Sentry MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Sentry 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.
AI-first code editor with integrated LLM-powered coding assistance.
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 Sentry to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.