Bring Full Stack Monitoring
to Vercel AI SDK
Learn how to connect Datadog to Vercel AI SDK and start using 16 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Datadog MCP Server?
Connect your Datadog account to any AI agent and take full control of your observability stack through natural conversation.
What you can do
- Monitor Management — List, search, inspect, and mute monitors to control alert noise during maintenance windows
- Dashboard Inspection — Browse dashboards and retrieve full layouts, widgets, and template variables
- Metric Queries — Run time-series queries using Datadog syntax (e.g.,
avg:system.cpu.user{*}) with custom time ranges - Log Search — Search log events using Datadog query syntax across all indexed log sources
- Event Tracking — Browse platform events and create custom events with tags and priority levels
- Incident Management — List active incidents with severity, status, responders, and timeline details
- SLO Monitoring — Review Service Level Objectives with targets, error budgets, and compliance status
- Host Inventory — Access all reporting hosts with metadata, tags, and agent versions
How it works
1. Subscribe to this server
2. Enter your Datadog API Key and your site URL (e.g., https://api.datadoghq.com for US or https://api.datadoghq.eu for EU)
3. Start monitoring your infrastructure from Claude, Cursor, or any MCP-compatible client
Who is this for?
- SRE / DevOps Engineers — query monitors, mute noisy alerts, and inspect incidents without opening the Datadog dashboard
- Platform Teams — run metric queries and validate SLO compliance through conversational AI
- On-Call Engineers — triage incidents, search error logs, and check host health during outages via natural language
Built-in capabilities (16)
Verify connectivity
Create an event
Get dashboard details
Get incident details
Get monitor details
List dashboards
List events
List hosts
List incidents
List metrics
List monitors
List SLOs
Mute a monitor
Query metric data
Search logs
Search monitors
Why Vercel AI SDK?
The Vercel AI SDK gives every Datadog tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 16 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
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Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Datadog integration everywhere
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Built-in streaming UI primitives let you display Datadog tool results progressively in React, Svelte, or Vue components
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Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Datadog in Vercel AI SDK
Datadog and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Datadog to Vercel AI SDK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Datadog in Vercel AI SDK
The Datadog 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. All 16 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Vercel AI SDK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Datadog for Vercel AI SDK
Every tool call from Vercel AI SDK to the Datadog MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I silence noisy monitors during scheduled maintenance?
Yes. The mute_monitor action silences a specific monitor by its ID, suppressing all alert notifications. This is ideal during deployment windows or planned maintenance. Use search_monitors to find the monitor by name or tag first, then mute it by ID.
Does Datadog require two credentials to connect?
Yes. You need your API Key (found in Organization Settings > API Keys) and your Base URL, which depends on your Datadog site region: https://api.datadoghq.com for US1, https://api.datadoghq.eu for EU, or https://api.us3.datadoghq.com for US3. The API Key is sent via the DD-API-KEY header.
Can I run time-series metric queries with custom time ranges?
Yes. The query_metrics tool accepts a Datadog metric query string (e.g., avg:system.cpu.user{host:web-01}), a start epoch timestamp, and an end epoch timestamp. It returns the time-series data points for that metric across the specified window.
How does the Vercel AI SDK connect to MCP servers?
Import 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?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp