Datadog MCP Server
for AI Agents
Connect your AI agent to StackOne's Datadog MCP server and give it 26 MCP tools out of the box. Auth, tool execution, and security all managed.
StackOne 
Coverage
26 Agent Actions
Create, read, update, and delete across Datadog — and extend your agent's capabilities with custom actions.
Authentication
Agent Tool Authentication
Per-user OAuth in one call. Your Datadog MCP server gets session-scoped tokens with zero credentials stored on your infra.
Agent Auth →
Security
Agent Protection
Every Datadog tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.
Prompt Injection Defense →
Performance
Max Agent Context. Min Cost.
Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every Datadog call.
Tools Discovery →What is the Datadog MCP Server?
A Datadog MCP server lets AI agents read and write Datadog data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Datadog MCP server ships with 26 pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, observability, and agent execution runtime. Connect it from MCP clients like Claude Desktop, Claude Code, Cursor, Goose, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.
All Datadog MCP Tools
Every action from Datadog's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.
Logs
- Search Logs
Search and filter Datadog logs using log search syntax.
- List Logs
List recent log events from Datadog with optional filtering.
Monitors
- Create Monitor
Create a new monitor to alert on metrics, logs, or other data sources.
- List Monitors
Get all monitors with optional filtering by name, tags, or state.
- Get Monitor
Get details about a specific monitor by its ID.
- Update Monitor
Edit an existing monitor's configuration, thresholds, or notification settings.
Service Definitions
- Create Service Definition
CREATE a new service definition or UPDATE an existing service definition in the Datadog Service Catalog. Use for creating, adding, or registering services.
- List Service Definitions
List all service definitions in the service catalog with ownership and metadata.
- Get Service Definition
Retrieve the service definition for a specific service by name.
- Delete Service Definition
Delete a service definition from the service catalog.
Spans
- Search Spans
Search and filter APM spans/traces for debugging performance issues with latency and error analysis.
- List Spans
Get a list of spans matching a search query with optional time range filtering.
Other (14)
- Create Log Index
Create a new log index in Datadog.
- List Log Indexes
Get all log indexes in the organization.
- List Active Metrics
Get the list of actively reporting metrics from a given time until now.
- Query Metrics
Query timeseries points to get actual metric data values over time.
- Get Metric Metadata
Get metadata about a specific metric.
- Get Metric Tag Configuration
Get the tag configuration for a specific metric.
- List Tags By Metric
View indexed and ingested tags for a given metric name.
- List Service Dependencies
Get all APM service dependencies showing upstream and downstream service relationships.
- List Retention Filters
Get the list of APM retention filters for your organization.
- Aggregate Logs
Compute aggregations and statistics over log data for pattern analysis and error counting.
- Submit Metrics
Submit custom metric data points to Datadog for graphing on dashboards.
- Timeseries Query
Query timeseries data across multiple products (metrics, logs, spans, etc.) with formulas and functions.
- Scalar Query
Get a single aggregated scalar value (not timeseries) from Datadog metrics. Returns one number like average CPU, total count, or max memory for dashboard widgets, alerts, and summary statistics.
- Aggregate Spans
Aggregate spans into buckets and compute metrics and timeseries for latency analysis.
Set Up Your Datadog MCP Server in Minutes
One endpoint. Any framework. Your agent is talking to Datadog in under 10 lines of code.
Agent Frameworks
JSON{
"mcpServers": {
"stackone": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://api.stackone.com/mcp?x-account-id=<account_id>",
"--header",
"Authorization: Basic <YOUR_BASE64_TOKEN>"
]
}
}
}Platform Resources
MCP Code Mode: Keeping Tool Responses Out of Agent Context
Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.
11 min
Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery
Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.
10 min
Indirect Prompt Injection Defense for MCP Tools: A Technical Guide
MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.
12 min
MCP vs A2A: Architecture, Security, and When to Use Each
MCP vs A2A: what each protocol standardizes, how they differ, their shared security risks including indirect prompt injection, and when to use one, both, or a hybrid architecture.
12 min
MCP vs API: What 200+ Connector Builds Taught Us
MCP wraps APIs, it doesn't replace them. After building 200+ connectors that serve both, here's when each approach wins.
14 min read
Datadog MCP Server FAQ
Does StackOne have a Datadog MCP server?
Datadog MCP server vs direct API integration — what's the difference?
How does Datadog authentication work for AI agents?
origin_owner_id.Are Datadog MCP tools vulnerable to prompt injection?
What is the context bloat of a Datadog agent and how do I avoid it?
Can I limit which actions my Datadog agent can access?
Can I create custom agent actions for my Datadog MCP server?
When should I NOT use a Datadog MCP server?
What AI frameworks and AI clients does the StackOne Datadog MCP server support?
Put your AI agents to work
All the tools you need to build and scale AI agent integrations, with best-in-class connectivity, execution, and security.