Scope
Built read-only MCP and CLI tooling for collecting profile, portfolio, Search Console, and GitLab evidence into structured local update packs.
LinkedIn Profile MCP & Portfolio Evidence Capture
Plain-English summary: Read-only MCP and CLI tooling for turning LinkedIn, portfolio, Search Console, and GitLab evidence into structured profile-update packs.
Technical Architecture
Problem/Context
- Profile and portfolio updates were too easy to base on memory instead of captured proof.
- LinkedIn, portfolio, GSC, and GitLab evidence needed one repeatable workflow with explicit safety limits.
- Account-private analytics and third-party state had to remain read-only and locally controlled.
What I Built
- Implemented CLI and MCP tools for profile PDF/live comparison, profile audits, browser capture, manual update packs, and portfolio/GSC evidence capture.
- Created reusable Codex skills for LinkedIn deep capture, Google Search Console capture, and portfolio evidence extraction.
- Added secret scanning, read-only guardrails, ignored local outputs, tests, and GitLab delivery hygiene.
Responsibilities
- I designed the evidence model, CLI commands, MCP tools, browser-capture boundaries, and reusable Codex skills.
- I kept owner-private LinkedIn analytics and account data out of public copy unless explicitly approved.
- I built the workflow to support profile updates without mutating LinkedIn, GSC, or GitLab state.
Constraints
- The repository and captures may include private account context, so public claims must stay bounded.
- No public adoption, external-user, or revenue claims are made.
- Private GitLab links, sessions, cookies, screenshots, and analytics remain unpublished.
Outcome/Value
- A repeatable evidence pipeline for making LinkedIn and portfolio updates from captured proof.
- A stronger safety model for AI-assisted profile work across browser, API, and local artifacts.
- A useful internal tool that supports SEO and AI-readable portfolio improvement without leaking private state.
System Concepts
- Read-only third-party automation.
- Evidence-first profile maintenance.
- Machine-readable portfolio and SEO context workflows.