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dbay-sre-mcp

MCP (Model Context Protocol) server exposing SRE-style log diagnostics over a Postgres-backed log store. Designed for use by LLM agents that need to query structured application logs.

Tools (0.2.1)

Log queries (PG-backed dbay-logs)

Tool Purpose
log_search Flexible keyword/component/time filter
log_trace Follow a request_id chain across components
log_errors Recent error-level lines with auto-aggregation
log_stats Activity overview by component / level / time

Metadata (lakeon-api admin REST)

Tool Purpose
find_database Resolve DB name → id + status + tenant + compute_host
find_tenant Resolve tenant name → id + held databases
database_status Comprehensive DB snapshot + last 1h cold-start + events

Consistency & queues (admin REST)

Tool Purpose
data_consistency_check Run named invariant rule (KB↔db_id, enqueued↔drained, etc.) via admin REST
stuck_task_query Async tasks in_progress beyond threshold via admin REST

Cluster signals (admin REST + dbay-logs)

Tool Purpose
pod_create_failures k8s pod-create failures aggregated by category
multi_tenant_blast_radius Single error pattern affecting N tenants in a window

Required env vars

Variable Used by Notes
LOG_DB_DSN log_*, multi_tenant_blast_radius dbay-logs Postgres connection string
LAKEON_ADMIN_TOKEN find_*, database_status, pod_create_failures, data_consistency_check, stuck_task_query Admin token for /admin/* endpoints
LAKEON_API_BASE_URL (above) default https://api.dbay.cloud:8443/api/v1

Install

pip install dbay-sre-mcp

Configure

Point at your Postgres log store via either:

  • LOG_DB_DSN environment variable, or
  • ~/.dbay/sre-config.json with key "dsn"

Expected logs table schema:

logs(id, ts, level, component, request_id, tenant_id, db_id, logger, msg, duration_ms, extra, thread)

Use as MCP server

dbay-sre-mcp

Then connect from any MCP-compatible client (Claude Code, Hermes, Codex, custom).

License

Apache-2.0

Metadata

Release files for dbay-sre-mcp 0.2.1

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Table of built distributions (wheels) for dbay-sre-mcp 0.2.1
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