datadog-logs-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DD_SITE | No | Datadog site (default: datadoghq.com). Use datadoghq.eu, us3.datadoghq.com, us5.datadoghq.com, etc. | datadoghq.com |
| DD_API_KEY | Yes | Datadog API key | |
| DD_APP_KEY | Yes | Datadog Application key |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_logsA | Search Datadog logs using the log search syntax. Returns matching log entries with their attributes, timestamps, and metadata. |
| get_logA | Retrieve a specific Datadog log entry by its unique ID. Requires the approximate timestamp of the log to narrow the search. |
| aggregate_logsA | Aggregate Datadog logs to compute metrics like count, avg, sum, min, max, percentiles. Supports group-by for breakdowns. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool targets a distinct operation: search_logs filters and returns multiple entries, get_log fetches a single entry by ID, and aggregate_logs computes metrics. There is no meaningful overlap, making tool selection unambiguous.
All tool names follow the same verb_noun snake_case pattern (search_logs, get_log, aggregate_logs), which is predictable and consistent across the set.
Three tools is a well-scoped count for a log-focused server. It covers the core operations (search, retrieve, aggregate) without unnecessary bloat or thinness.
The set covers the primary log reading and analysis workflow: searching, fetching by ID, and aggregating metrics. Minor gaps like log index listing or log ingestion are absent but not essential for the apparent purpose.