Integrations
Discover GCP-hosted AI agent and MCP-relevant assets from the operator's environment, emit canonical agent-bom inventory JSON, and scan it without giving agent-bom long-lived GCP credentials. Use when a user asks to inventory Vertex AI, Cloud Run, Cloud Functions, GKE, or agentic GCP infrastructure as canonical inventory.
Discover GCP-hosted AI agent and MCP-relevant assets from the operator's environment, emit canonical agent-bom inventory JSON, and scan it without giving agent-bom long-lived GCP credentials. Use when a user asks to inventory Vertex AI, Cloud Run, Cloud Functions, GKE, or agentic GCP infrastructure as canonical inventory.
Use this skill to collect GCP AI and workload inventory as schema-valid agent-bom inventory. Default to discover-only: write JSON to an operator-selected path and stop.
python examples/operator_pull/gcp_inventory_adapter.py \
--project "$GOOGLE_CLOUD_PROJECT" \
--region us-central1 \
--source gcp-skill-invoked \
--discovery-method skill_invoked_pull \
--output gcp-inventory.json
Scan only when the operator asks for findings:
agent-bom scan --inventory gcp-inventory.json --format json --output agent-bom-gcp-findings.json
The emitted inventory carries discovery_provenance.source_type: skill_invoked_pull, observed_via: skill_invoked_pull, gcp_sdk, sanitized
metadata.permissions_used, and redacted credential material. If schema
validation fails, stop and fix the inventory instead of scanning a best-effort
summary.
Discover Azure-hosted AI agent and MCP-relevant assets from the operator's environment, emit canonical agent-bom inventory JSON, and scan it without giving agent-bom long-lived Azure credentials. Use when a user asks to inventory Azure OpenAI, Container Apps, AKS, Functions, ML, or agentic Azure infrastructure as canonical inventory.
Discover AWS-hosted AI agent and MCP-relevant assets from the operator's environment, emit canonical agent-bom inventory JSON, and scan it without giving agent-bom long-lived cloud credentials. Use when a user asks to inventory AWS Bedrock, ECS, SageMaker, Lambda, EKS, Step Functions, EC2, or agentic AWS infrastructure as canonical inventory. Passing that inventory to agent-bom is optional and operator-chosen.
Validate and ingest operator-pushed agent-bom inventory JSON from AWS, Azure, GCP, Snowflake, CMDB, or endpoint collectors. Use when a user has canonical inventory JSON and wants local findings, graph, policy, provenance, or auditor-ready exports without giving agent-bom direct cloud credentials.
Discover Snowflake Cortex, Snowpark, notebook, Streamlit, MCP, and AI-observability assets from the operator's environment, emit canonical agent-bom inventory JSON, and scan it without giving agent-bom long-lived Snowflake credentials. Use when a user asks to inventory Snowflake AI or Cortex infrastructure as canonical inventory.
MCP server security registry and trust assessment — look up servers in the 1123-entry server security metadata registry, run pre-install marketplace checks, batch fleet risk scoring, assess skill file trust, and run SAST code scans. Use when the user mentions MCP server trust, registry lookup, marketplace check, or skill trust assessment.
AI runtime security monitoring — context graph analysis, runtime audit log correlation with CVE findings, and vulnerability analytics queries. Use when the user mentions runtime monitoring, context graphs, lateral movement analysis, audit log correlation, or vulnerability analytics.