ContextOps AI Engine v1.0 is live

The autonomous incident responder for modern SRE teams.

Don't just route alerts. Resolve them. ContextOps connects your infrastructure telemetry directly to your source code, diagnosing root causes in seconds.

Start Investigating Star on GitHub

The ContextOps Advantage

Stop treating symptoms. We designed this engine to completely eliminate the first 30 minutes of incident triage for on-call engineers.

ContextOps Scope
Built to autonomously triage and synthesize production outages.
Why Developers Need This
Eliminate the manual toll of context gathering during 3 AM pages.

➜ agent run --incident-id 9821

Initializing LangGraph...

mcp-github attached

mcp-datadog attached

Synthesizing root cause...

How It Operates
Webhooks trigger a LangGraph agent equipped with MCP tools.
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PagerDuty Trigger

Incident

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Sreejesh - Lead Architect

Developer

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AI Context Engine

Agentic

Built by Sreejesh
Developed as an advanced AI incident engine demonstrating modern AIOps capabilities.
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Manual incident triage wastes an average of 30 minutes gathering context across Datadog, GitHub, and runbooks...

Automate it.

Extensible Architecture
Not just GitHub. Plug into Datadog, AWS, and Stripe seamlessly.

How ContextOps Works

The autonomous pipeline from infrastructure failure to code-level fix.

Datadog
PagerDuty

Alert Triggers

PagerDuty or Datadog fires a webhook containing raw symptom data.

GitHub

AI Contextualizes

The agent queries GitHub, tracing the failing service back to recent commits.

Root Cause Synthesized

The dashboard streams the exact mitigation steps for the on-call engineer.

Powered by the Model Context Protocol

ContextOps is built on an extensible MCP architecture. It dynamically loads plugins for any operational tool you use, adapting to any outage.

GitHubGitHub
DatadogDatadog
KubernetesKubernetes
GrafanaGrafana
PagerDutyPagerDuty
OpsgenieOpsgenie
LinearLinear
PostgreSQLPostgreSQL