A production-grade, self-hosted automation ecosystem turning a vast library of complex n8n workflow JSON pipelines into an instantly searchable, categorized, and exportable engineering catalog powered by FastAPI, SQLite FTS5, and Docker.
Modern marketing and growth operations rely on dozens of disparate SaaS applications—ad networks, CRM databases, email deliverability tools, and LLM APIs. Connecting these through custom point-to-point glue code creates high maintenance overhead, fragile single points of failure, and zero central visibility.
Conversely, when teams adopt low-code workflow platforms like n8n, they rapidly accumulate hundreds of raw JSON workflow files. Without a structured catalog or discovery layer, developers and growth engineers face severe friction:
Raw JSON export files cannot be searched across node configurations, webhook endpoints, or credentials without opening every file manually.
Different growth pods recreate the exact same Meta CAPI or lead-enrichment workflows from scratch rather than reusing hardened templates.
Unvetted community workflows frequently include unvalidated webhook params, unencrypted API tokens, and missing CORS or rate limits.
When webhook payloads fail silently, growth teams lose critical conversion events and attribution tracking without immediate alerts.
I engineered a production catalog and API microservice that transforms thousands of isolated n8n workflow JSON files into an indexed, discoverable product surface. Backed by FastAPI, an SQLite FTS5 (Full-Text Search) engine, and Docker containerization, it enables instantaneous keyword lookup, complexity filtering, and verified JSON exports.
Tokenizes all node types, descriptions, triggers, and integration tags into an embedded SQLite full-text search table for sub-50ms queries.
Clean REST endpoints (/api/search, /api/workflow/:id, /api/export/:id) with Pydantic schema validation and rate limiting.
Strict path traversal sanitization, CORS allowlisting, non-root Docker execution user, and automated Trivy vulnerability checks.
Ingestion → Tokenization → Query Execution → Secure JSON Delivery
Pipelines created in n8n (or authored as JSON specifications) are ingested from the static repository structure. Each file is parsed to extract metadata: node types, trigger mechanisms, and integration connectors.
A standalone Python indexing pipeline (`workflow_db.py`) creates a high-performance SQLite virtual table (`workflows_fts`). Text fields are tokenized with Porter stemming for rapid substring and semantic matching.
The FastAPI query parser evaluates parameters: `category` (Marketing, SEO, DevOps), `trigger` (Webhook, Cron, Poll), `complexity` (Beginner to Expert), and `services` (Stripe, Meta, Slack, OpenAI).
Engineers view full node topologies, credential requirements, and parameter mappings in the browser UI, then copy or export clean JSON directly into their local or cloud n8n instances.
High-Resolution Screenshot of Active n8n Automation Mesh

Real-world n8n execution canvas illustrating webhook data ingestion, conditional data branching, AI enrichment, and multi-endpoint notifications.
Sample Workflows from the Catalog Repository
Receives form webhooks, hashes PII (SHA-256), checks SQLite dedup table, and dispatches to Meta Conversions API.
Polls Google Search Console performance data for >3 position drops, queries Anthropic for remediation brief, and notifies editorial desk.
Intercepts charge.succeeded events, correlates anonymous session cookie ID, and attributes touchpoint weights.
Parses complex natural-language business requests, assigns work to departmental agent pods, and aggregates responses.
Validates corporate email MX records, checks company employee count, and tags SDR priorities in real-time.
Executes simulated headless browser login flow; triggers PagerDuty escalation if selector fails within 5,000ms.
Verified from api_server.py, workflow_db.py & Dockerfile
The catalog microservice separates data storage, search querying, and frontend rendering into cleanly decoupled layers:
Ground-Truth Engineering Assertions (Source Seed Compliance)
How Growth Flow Operationalizes Other Growth Systems
Supplies rank-drop and CTR-anomaly triggers that initiate n8n content triage webhooks.
Executes marketing workflow pipelines deployed from Growth Flow templates across CRM and ad channels.
Exposes Growth Flow search and workflow retrieval endpoints as MCP tool calls for Claude and Cursor.
Virtual office agents trigger pre-tested n8n background automations for recurring business workflows.
Growth Flow functions as the connective tissue across the portfolio: feeding alerts from Search Intelligence into Content Generation, and piping attribution data back to CRM databases.
I'm open to Digital Growth, Technical SEO, SaaS, AI Automation, and Analytics opportunities.