Datadog MCP server for Claude, ChatGPT, Claude Code and Cursor
Datadog offers monitoring, observability, and security for cloud-scale applications, unifying metrics, logs, and traces to help teams detect issues and optimize performance
Examples of what your AI apps can do in Datadog. You'll see the exact list of tools after you connect it.
create_dashboard
ToolCreate a dashboard in datadog. dashboards provide customizable visualizations for monitoring your infrastructure, applications, and business metrics in a unified view.
create_downtime
ToolCreates a new downtime in datadog to suppress alerts during maintenance windows or planned outages. useful for preventing false alarms during deployments or maintenance.
create_monitor
ToolCreates a new datadog monitor to track metrics, logs, or other data sources with configurable alerting thresholds and notifications.
create_slo
ToolCreate a service level objective (slo) in datadog. slos help you define and track reliability targets for your services, enabling data-driven decisions about service quality and reliability investments.
create_synthetic_api_test
ToolCreate a synthetic api test in datadog. creates a new synthetic api test that continuously monitors api endpoints from multiple locations worldwide. useful for proactive monitoring of api uptime, performance, and functionality.
create_webhook
ToolCreate a webhook in datadog. webhooks enable you to receive notifications from datadog monitors and alerts to external services and applications.
delete_dashboard
ToolDelete a dashboard in datadog. permanently removes a dashboard from your organization. this action cannot be undone. use with caution.
get_dashboard
ToolGet a specific dashboard from datadog. retrieves detailed information about a dashboard including its widgets, layout, template variables, and metadata.
get_service_dependencies
ToolGet service dependency mapping from datadog apm. this action retrieves the dependency graph for a specific service, showing both upstream services (that call this service) and downstream services (that this service calls). it's essential for: - understanding the blast radius of service failures - identifying critical dependencies during incidents - analyzing service communication patterns - planning architectural changes - monitoring service health in context the dependency information includes call rates, error rates, and latency metrics to help assess the health of service relationships.
get_synthetics_locations
ToolTool to retrieve all available public and private locations for synthetic tests in datadog. use when you need a list of location identifiers for creating or managing synthetic tests.
get_tags
ToolRetrieves all tags associated with a specific host in datadog. useful for understanding host metadata and organizing infrastructure.
get_trace_by_id
ToolGet detailed information about a specific trace by its id. this action retrieves comprehensive details about a distributed trace, including all spans, timing information, errors, and metadata. it's essential for: - deep diving into specific request flows during incidents - understanding the complete journey of a problematic request - analyzing performance bottlenecks in detail - correlating errors across services - debugging complex distributed system issues the trace id is typically obtained from logs, error reports, or trace search results.
list_all_tags
ToolList all tags from datadog. tags help organize and filter your infrastructure and applications. this action shows all tags in use across your organization.
list_api_keys
ToolList api keys in datadog. retrieves all api keys in the organization for security auditing, access management, and key rotation planning. helps maintain security posture by tracking key usage and ownership.
list_apm_services
ToolList apm services from datadog. application performance monitoring (apm) provides deep visibility into your applications, helping you track performance, errors, and dependencies.
list_aws_integration
ToolList aws integrations in datadog. retrieves all configured aws account integrations, showing which aws accounts are monitored by datadog and their configuration settings. useful for cloud infrastructure management and ensuring comprehensive monitoring coverage.
list_incidents
ToolList incidents from datadog. incident management helps you track, manage, and resolve incidents efficiently with comprehensive timeline and impact tracking.
list_log_indexes
ToolTool to retrieve a list of all log indexes configured in datadog. use when you need to get the names and configurations of log indexes.
list_monitors
ToolGet all monitor details. this endpoint allows you to retrieve information about all monitors configured in your organization. you can filter by group states, name, tags, and use pagination to manage large result sets.
list_roles
ToolList roles from datadog organization. roles define sets of permissions that control what users can do within your datadog organization.
list_sl_os
ToolList service level objectives (slos) from datadog. service level objectives help you track the reliability and performance of your services by setting measurable targets for key metrics.
list_synthetics
ToolList synthetics tests from datadog. synthetics monitoring allows you to proactively monitor your applications and apis by simulating user interactions and api calls from various locations.
list_users
ToolList users from datadog organization. user management allows you to see team members, their roles, and access levels within your datadog organization.
list_webhooks
ToolList webhooks from datadog. webhooks allow you to send notifications to external services when monitors trigger, enabling integration with your workflows.
mute_monitor
ToolMute a monitor in datadog. temporarily silences alerts from a monitor, which is useful during maintenance windows, deployments, or when investigating known issues to prevent alert fatigue.
query_metrics
ToolQueries datadog metrics and returns time series data. useful for retrieving historical metric data, creating custom dashboards, or building reports.
search_logs
ToolSearches datadog logs with advanced filtering capabilities. important notes: - sort parameter is not supported by the datadog logs api and will cause errors - time parameters must be in milliseconds (13-digit unix timestamps) - limit parameter is passed as string to the api - log content is nested under 'content' field in api response useful for troubleshooting, monitoring application behavior, and analyzing log patterns.
search_spans_analytics
ToolSearch and analyze span data with aggregations in datadog. this action uses the datadog spans analytics api to perform advanced queries and aggregations on trace span data. it's essential for: - analyzing error rates and latency patterns - understanding service dependencies and bottlenecks - root cause analysis during incidents - performance monitoring and optimization the api supports complex queries with grouping, filtering, and various aggregation functions similar to log analytics.
search_traces
ToolSearch for traces in datadog apm. this action allows you to search for distributed traces across your services. it's essential for: - finding specific request flows during incident investigation - analyzing performance bottlenecks across services - understanding error propagation through your system - correlating user requests with backend operations traces provide the complete picture of a request as it travels through your distributed system, making them crucial for root cause analysis.
submit_metrics
ToolSubmits custom metrics to datadog. useful for sending application-specific metrics, business kpis, or custom performance indicators.
unmute_monitor
ToolUnmute a monitor in datadog. re-enables alerts from a previously muted monitor, returning it to normal monitoring and alerting behavior. use this after maintenance windows or issue resolution to resume monitoring.
update_dashboard
ToolUpdate a dashboard in datadog. updates an existing dashboard with new configuration, widgets, or layout while preserving its identity and creation metadata.
create_event
ToolCreates a new event in datadog. events are useful for tracking deployments, outages, configuration changes, and other important occurrences.
delete_monitor
ToolDeletes a datadog monitor permanently. use with caution as this action cannot be undone.
get_monitor
ToolRetrieves detailed information about a specific datadog monitor, including its current state, configuration, and any active downtimes.
get_usage_summary
ToolRetrieves usage summary information from datadog including api calls, hosts, containers, and other billable usage metrics. useful for cost monitoring and usage analysis.
list_dashboards
ToolLists all datadog dashboards with basic information. useful for dashboard management and getting an overview of available dashboards.
list_events
ToolLists events from datadog within a specified time range. events track important occurrences like deployments, outages, and configuration changes.
list_hosts
ToolLists all hosts in your datadog infrastructure with detailed information including metrics, tags, and status. useful for infrastructure monitoring and management.
list_service_checks
ToolLists service checks from datadog. service checks are status checks that track the health of your services and infrastructure components.
update_host_tags
ToolUpdates tags for a specific host in datadog. this replaces all existing tags from the specified source with the new tags provided.
update_monitor
ToolUpdates an existing datadog monitor with new configuration, thresholds, or notification settings. only specified fields will be updated.
Free. No card needed.
How to connect Datadog
- 1Create your free ContextGate account.
- 2Datadog isn't in ContextGate's app list yet. If you have an MCP server for Datadog, add it under Connections → Add Connection → Custom MCP.
- 3Add ContextGate to Claude, Cursor or ChatGPT (the Setup page shows you how), then ask it to use Datadog.
What you get with Datadog and ContextGate
- Your AI apps can use Datadog Claude, Cursor, ChatGPT and other AI apps reach Datadog through the one ContextGate connection you add to them.
- You choose which tools they can use Switch off any Datadog tool you don't want used. It's hidden from your AI apps and refused if called.
- Every call is checked and recorded Your policies check each call (for example, personal data is hidden and secrets are blocked), and Activity keeps a record of it.
ContextGate sees only the tool calls that go through it, not your AI app's built-in tools or your chats.
Select a tool on the left to see its parameters
What you get with Datadog and ContextGate
- Your AI apps can use Datadog: Claude, Cursor, ChatGPT and other AI apps reach Datadog through the one ContextGate connection you add to them.
- You choose which tools they can use: Switch off any Datadog tool you don't want used. It's hidden from your AI apps and refused if called.
- Every call is checked and recorded: Your policies check each call (for example, personal data is hidden and secrets are blocked), and Activity keeps a record of it.
ContextGate sees only the tool calls that go through it, not your AI app's built-in tools or your chats.
Free. No card needed.
How to connect Datadog
- Create your free ContextGate account.
- Datadog isn't in ContextGate's app list yet. If you have an MCP server for Datadog, add it under Connections → Add Connection → Custom MCP.
- Add ContextGate to Claude, Cursor or ChatGPT (the Setup page shows you how), then ask it to use Datadog.