Overview

Connect Cleric to your infrastructure

Cleric uses standard CLIs and APIs (kubectl, gh, aws, etc.) to query your infrastructure. An Integration is a credential configuration that authenticates Cleric with a specific system.

You provide credentials once (API keys, tokens, service accounts), and Cleric uses them for all investigations. Most integrations require read-only access, though for some we suggest certain write permissions for enhanced functionality.

Supported Capabilities

The table below shows what data Cleric can access from each integration.

Integration	Data Type	Example Tasks	Common Use Cases
Amazon Web Services	Logs	Query CloudWatch logs	Debugging applications, analyzing Lambda executions
	Metrics	Query CloudWatch metrics	Resource utilization, performance monitoring
	Resources	Describe EC2 instances, ELBs, Route 53 DNS, ACM certificates	Infrastructure state, DNS configuration, certificate management
Confluence	Documentation	Retrieve pages from a space, get content of a page	Runbooks, architecture documentation
Jira	Issues	Search issues, get issue details with comments and attachments	Incident history, ticket context
	Actions	Create issues (requires "Create Issues" permission)	Filing tickets from investigation findings
Datadog	Metrics	Query metrics, list metrics, get metric details	Detecting anomalies, performance degradation
	Logs	Search and analyze logs, get service tags from logs	Identifying application errors
	Monitors	Get monitor details	Understanding alert context
	Dashboards	List dashboards by URL or title	Leveraging existing team context
	SLOs	Get SLO details	Tracking service reliability
Elastic Kubernetes Service	Events	List events	Detecting deployment issues
	Logs	Search logs for pods	Identifying application errors, startup issues
	Resources	List, get, and describe resources (pods, deployments, etc.)	Detecting deployment issues, pod crashes, scaling problems
	Metrics	Get CPU/memory usage for pods and nodes	Resource contentions, quota exceedances
Elasticsearch	Search Indices	List indices, get field mappings	Understanding data structure
	Logs	Search with query DSL	Searching application logs, analyzing indexed data
GitHub	Repositories	Get code diff, get commit history, search code, create branches	System context, change history, proposed fixes
	Issues & PRs	Create issues, open pull requests	Tracking problems, proposing code changes
	Logs	Analyze workflow logs	Identifying deployment errors
Google Cloud Platform	Logs	Search and filter logs, retrieve log labels	Debugging applications, monitoring cloud infrastructure
	Metrics	Query Cloud Monitoring metrics	Resource utilization, performance monitoring
	Resources	Describe Compute instances, Load Balancers, Cloud DNS, Certificate Manager	Infrastructure state, DNS configuration, certificate management
Grafana	Metrics	Query metrics	Detecting anomalies, performance degradation
	Logs	Search Loki logs	Identifying application errors
	Alert Rules	List alert rules, get alert rule details by UID	Understanding alert context
	Dashboards	Get dashboard by UID	Leveraging existing team context
Kubernetes	Events	List events	Detecting deployment issues
	Logs	Search logs for pods	Identifying application errors, startup issues
	Resources	List, get, and describe resources (pods, deployments, etc.)	Detecting deployment issues, pod crashes, scaling problems
	Metrics	Get CPU/memory usage for pods and nodes	Resource contentions, quota exceedances
PagerDuty	Incidents	Get incident details	Alert patterns, on-call load analysis
	Services	Get service details	Understanding service health
Prometheus	Metrics	Query metrics, list metrics, get metric details	Performance monitoring, resource usage
	Alert Rules	Get active alert rules, get alert rule details	Understanding alert context
Generic MCP	Custom	Tools defined by the connected MCP server	Extending Cleric with custom data sources

MCP Support

Cleric integrates with the Model Context Protocol (MCP) in two directions:

• Generic MCP (Cleric as MCP client): Cleric connects to an MCP server you run and calls its tools during investigations. See the Generic MCP section of Supported Integrations.

• Cleric MCP Server (Cleric as MCP server): Cleric exposes an MCP endpoint at /mcp that AI coding tools such as Claude Code and Cursor connect to for reading investigation data and creating new investigations. Authenticates with a per-user API key generated from the Settings page. See MCP Server for setup.

Monitoring Integration Health

Cleric runs a read-only health check against each configured integration every hour. It tests the connection to the integration's API using the stored credentials.

Each integration on the Integrations page displays a status badge:

• Connected: The last health check succeeded within the past 2 hours

• Error: No successful health check in the past 2 hours, or the most recent connection test failed

When any enabled integration is in the "Error" state, a red indicator appears on the Integrations tab in the sidebar. Open the Integrations page to identify which integration is failing.

Common Causes of Health Check Failures

• Expired or rotated API tokens/credentials

• Network connectivity changes (firewall rules, IP allowlists)

• The external service is temporarily unavailable

• Credential permissions were revoked

To fix a failing integration, update the credentials and click Update configuration to save.

Enabling and Disabling Integrations

Each integration has an Enable configuration toggle at the bottom of its configuration form. Disabled integrations are not used during investigations and are not health-checked. They display a Disabled badge.