Momenul Ahmad
(He/Him)
Covers:
Topics: digital marketing landscape, Programming, software and extensions.
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Founder at www.seosiri.com
CAPEX Architect: capex.seosiri.com
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Momenul Ahmad’s Biography
Read Full Bio →Hi, I’m Momenul Ahmad — Digital Marketing Strategist & SEO Consultant
🚀 SEO Enthusiast | Growth-Focused Marketer | HubSpot Community Contributor
I’m a results-driven digital marketing strategist with a strong focus on SEO, content optimization, and data-driven growth. Over the years, I’ve helped businesses improve their organic visibility, conversion performance, and customer engagement through ethical and scalable digital marketing strategies.
As the founder of SEOSiri, I’ve led SEO-focused in…
Momenul Ahmad’s Journalist Portfolio
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43 Costly SEO Mistakes Businesses Still Make in 2025
Articles
Secure Live Data Querying & Cloud Infrastructure Control: The SEOSiri DB Infra MCP Server Architecture
Granting AI agents direct execution access to live cloud infrastructure requires strict, read-only guardrails and automated column-level PII masking. The open-source seosiri-db-infra-mcp server provides a local-first Model Context Protocol control plane to execute read-only PostgreSQL queries, inspect live database schema trees, audit AWS S3 bucket security, and monitor Cloudflare Worker edge deployments.
SEOSiri Model Context Protocol (MCP) infrastructure
AI agents are taking action—crawling websites, querying databases, handling biotech assays, and triggering physical workflows. Without local-first policy planes, AI models risk leaking PII, hallucinating answers, or triggering unsafe hardware actions. To solve this, we’ve open-sourced and deployed a sovereign 5-part SEOSiri Model Context Protocol (MCP) infrastructure.
Sovereign Data Engineering: The SEOSiri MCP-Native ETL Pipeline Architecture
A deep technical guide to deploying a local-first, multi-source ETL/ELT data orchestrator using Python, FastMCP, and PyPI. Lead Architect: Momenul Ahmad | Organization: SEOSiri-Official | Package Registry: PyPI (etl-pipeline-mcp) Connecting AI agents directly to production data streams often introduces unseen security risks and brittle pipelines.
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