Retrieve alerts from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Check currently active alerts

• Get a list of alerts including closed alerts

Get all alerts

list_alerts(withClosed=true)

Retrieve a specific alert by ID from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Investigate a particular alert

Retrieve logs for a specific alert by ID from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• View status change history for a specific alert

• Investigate alert transitions and their reasons

Retrieve all dashboards from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Get a list of dashboards

• Get ID and title of each dashboard

Retrieve a specific dashboard by ID from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Get details of a specific dashboard

• View dashboard configuration and widgets

Update a specific dashboard by ID in Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Modify dashboard title, memo, or URL path

• Update dashboard widgets configuration

Retrieve hosts from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Get a list of hosts

• Filter hosts by various criteria (service, role, name, etc.)

• Check host status and information

Get hosts for a specific role

list_hosts(service="web",role=["app"])

Get hosts by status with pagination

list_hosts(status=["working","standby"], limit=10, offset=0)

Get hosts in summary format (reduced response size)

list_hosts(summary=true)

Get next page of hosts

list_hosts(limit=20, offset=20)

Retrieve metrics data for a specific host from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Get metrics data for a specific host

• Analyze host performance over time

📊 AVAILABLE METRIC NAMES:

• Standard metrics (mackerel-agent): loadavg5, cpu.user, memory.used, disk.sda1.reads, network.eth0.rxBytes, etc.

• Custom metrics: custom.myapp.* (user-defined metrics)

• AWS integration: ec2.cpu.used, rds.database_connections.used, etc.

• Azure integration: azure.virtual_machine.cpu.percent, azure.sql_database.cpu.percent, etc.

• GCP integration: gce.instance.cpu.used, etc.

Get custom metric

get_host_metrics(hostId="host123", name="custom.myapp.response_time", from=1609459200, to=1609462800)

Get AWS EC2 CPU utilization

get_host_metrics(hostId="host123", name="ec2.cpu.used", from=1609459200, to=1609462800)

Retrieve all services from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Get a list of services

• View service names, memos, and roles

Retrieve metrics data for a specific service from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• "Service metrics" are metrics that correspond to a service that consists of multiple hosts and their collective roles

• The following can be visualized and monitored.

  • The total number of registered users in a service

  • The number of PVs for a website

  • Business related KPIs such as sales or the number of orders received from EC sites

📊 AVAILABLE METRIC NAMES:

• Custom metrics: http.response_time, sales.count, analytics.page_view, etc.

Get service page views

get_service_metrics(serviceName="web", name="analytics.page_view", from=1609459200, to=1609462800)

Retrieve all monitor configurations from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Get a list of all monitors

• View monitor configurations

Retrieve a specific monitor configuration by ID from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Get details of a specific monitor

Retrieve trace data by trace ID from Mackerel for distributed tracing analysis.

🔍 USE THIS TOOL WHEN USERS:

• Analyze performance bottlenecks in distributed systems

• Investigate error propagation across microservices

• Understand request flow and service dependencies

• Debug latency issues and identify slow operations

• Generate documentation of system architecture from trace data

Focus on errors only

get_trace(traceId="abc123def456", errorSpansOnly=true)

Filter spans with duration over 100ms

get_trace(traceId="abc123def456", duration=100)

Detailed analysis with attributes

get_trace(traceId="abc123def456", includeAttributes=true, limit=50)

Minimal view for overview

get_trace(traceId="abc123def456", includeEvents=false, limit=10)

Pagination through large traces

get_trace(traceId="abc123def456", limit=20, offset=0)  # First page
get_trace(traceId="abc123def456", limit=20, offset=20) # Second page

Combined filtering and pagination

get_trace(traceId="abc123def456", errorSpansOnly=true, limit=10, offset=0)

Search and retrieve traces from Mackerel for distributed tracing analysis.

🔍 USE THIS TOOL WHEN USERS:

• Search for traces within a time range

• Find slow traces by latency filtering

• Filter traces by service, environment, or version

• Investigate distributed system behavior

Filter by latency

list_traces(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  minLatencyMillis=100,
  maxLatencyMillis=1000
)

Filter by environment and version

list_traces(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  environment="production",
  version="v1.2.3"
)

Search by span name

list_traces(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  spanName="HTTP GET /api/users"
)

Pagination and sorting

list_traces(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  page=2,
  perPage=50,
  order={ column: "LATENCY", direction: "DESC" }
)

Retrieve HTTP server statistics from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Analyze slow HTTP endpoints

• Identify high-traffic routes

• Monitor error rates for HTTP requests

• Investigate API performance issues

Filter by environment and version

list_http_server_stats(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  environment="production",
  version="v1.2.3"
)

Filter by HTTP method and route

list_http_server_stats(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  method="GET",
  route="/api/users"
)

Pagination

list_http_server_stats(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  page=2,
  perPage=50
)

Retrieve database query statistics from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Analyze slow database queries

• Identify high-frequency queries

• Investigate database performance issues

• Monitor query execution patterns

Filter by environment and version

list_db_query_stats(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  environment="production",
  version="v1.2.3"
)

Search for specific queries

list_db_query_stats(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  query="SELECT * FROM users"
)

Pagination

list_db_query_stats(
  serviceName="my-service",
  from=1700000000,
  to=1700001800,
  page=10,
  perPage=50
)

Search logs of a service from Mackerel.

🔍 USE THIS TOOL WHEN USERS:

• Investigate errors or incidents by reading application logs

• Find logs related to a specific trace (traceId)

• Look for logs containing specific keywords or matching structured (JSON) body fields

📏 KEEPING RESPONSES SMALL:

• Pass serviceNamespace when the service has one. Without it, only services without a namespace are searched

• Omit from / to to search relative to the current time (lookbackMinutes, default 60). The response includes the actual timeRange searched

• Narrow the time range and use severities / keywords / bodyAttributes filters first

• By default only timestamp, severity, body, traceId and spanId are returned. Use fields to request attributes only when needed

• Log bodies longer than maxBodyLength are truncated and marked with bodyTruncated: true

• To get more logs, pass pagination.nextPageCursor as pageCursor as-is with the same filters. The cursor carries the time range and sort order, so from / to / order are not needed. The API allows 1 request per second

Logs in the last 15 minutes

search_logs(serviceName="my-service", serviceNamespace="my-namespace", lookbackMinutes=15)

Logs related to a trace in chronological order

search_logs(serviceName="my-service", serviceNamespace="my-namespace", from=1700000000, to=1700003600, traceId="0af7651916cd43dd8448eb211c80319c", order="ASC")

Keyword search

search_logs(serviceName="my-service", serviceNamespace="my-namespace", from=1700000000, to=1700003600, keywords=["timeout", "payment"])

Filter JSON bodies: {"res": {"status": 500+}}

search_logs(
  serviceName="my-service",
  serviceNamespace="my-namespace",
  from=1700000000,
  to=1700003600,
  bodyAttributes=[{keyPath: ["res", "status"], value: "500", type: "int", operator: "GTE"}]
)

Include log attributes

search_logs(serviceName="my-service", serviceNamespace="my-namespace", from=1700000000, to=1700003600, fields=["timestamp", "body", "attributes", "resourceAttributes"])

Next page

search_logs(serviceName="my-service", serviceNamespace="my-namespace", severities=["ERROR"], pageCursor=<pagination.nextPageCursor>)