personal-context

Turn your digital footprint into an AI-readable profile. GitHub + Blogs + Resume + Notes -> one context source for every AI agent.

<p align="center"> <img src="docs/demo.gif" alt="personal-context CLI demo" width="760" /> </p>

[!NOTE] Work in progress — something crazy on the way. ✦

Documentation: https://ayush7614.github.io/personal-context/

Current AI tools forget who you are. You keep re-explaining your work, skills, projects, blogs, and open-source contributions. personal-context aggregates all of it from your real sources and outputs it as a single profile you can print, share, or feed to any AI tool (Cursor, Claude Code, Codex, Gemini CLI).

$ npx personal-context all

Ayush Kumar
DevRel · AI Agents · Open Source · AI Security

Current Role:
  Lead Developer Relations Engineer @ NodeShift AI Cloud

Contact:
  Email: ayushknj3@gmail.com
  GitHub: https://github.com/Ayush7614

Recent Blogs:
  - AI Agents Masterclass — Full Visual Guide
  - Harness Engineering — Full Visual Guide
  ...

GitHub:
  Contributions: 1250
  Repositories: 35
  ...

Quick start

# 1. Scaffold a config in the current folder
npx personal-context init

# 2. Edit personal.yaml with your details + source handles

# 3. See your full profile
npx personal-context all

# 4. Generate AI-readable files (context.md, profile.json, llms.txt)
npx personal-context build

Commands

Command	Description
init	Create a starter personal.yaml
teaser (wip)	Animated "something crazy on the way" splash
all	Full profile overview (the single-command output)
github	GitHub stats + latest contributions
blogs [--limit N]	Recent posts across all RSS feeds
linkedin	Role + experience timeline
opensource (oss)	Open-source contributions
build [--out dir]	Write context.md, profile.json, llms.txt
summary	One-paragraph AI brief

Every read command supports --json for piping into other tools.

Configuration

Everything is driven by a single personal.yaml (see personal.yaml for a full reference). Static facts (name, role, skills, projects) live in the file; live data is pulled from the sources you configure:

Information	Source
GitHub contributions, PRs, repos	GitHub REST + GraphQL API
Latest blogs	RSS feeds (Medium, Hashnode, Dev.to)
Experience timeline	personal.yaml + LinkedIn export (JSON)
Resume skills / summary	Resume JSON or PDF

Set GITHUB_TOKEN (see .env.example) to unlock contribution counts and higher rate limits.

MCP server

personal-context also ships an MCP server so any AI agent (Cursor, Claude Code, Codex, etc.) can query your context live.

Add it to your MCP client config (e.g. Cursor's ~/.cursor/mcp.json):

{
  "mcpServers": {
    "personal-context": {
      "command": "npx",
      "args": ["-y", "personal-context-mcp"],
      "env": {
        "PERSONAL_CONTEXT_CONFIG": "/absolute/path/to/personal.yaml",
        "GITHUB_TOKEN": "optional-token"
      }
    }
  }
}

Then your agent can call:

Tool	Returns
get_profile	The full profile object
get_summary	One-paragraph AI brief
get_recent_blogs { limit }	Recent posts across feeds
get_github_stats	Contributions, PRs, repos, top repos
get_projects	Projects you build/ship
get_open_source	Open-source contributions
get_contact_info	Email, website, socials
get_learning_history	What you're learning + skills

PERSONAL_CONTEXT_CONFIG points the server at your personal.yaml regardless of the directory the client launches it from.

Architecture

A pnpm monorepo with a shared core so the CLI, the MCP server, and your portfolio all consume the same profile data.

personal-context/
├── packages/
│   ├── core/   # sources + aggregation + renderers (Profile, context.md, llms.txt)
│   ├── cli/    # the `personal-context` command
│   └── mcp/    # the `personal-context-mcp` MCP server
└── personal.yaml

Roadmap

• v1 — Core + CLI (GitHub, blogs, LinkedIn, resume, generated profiles) ✅
• v2 — MCP server (get_profile, get_recent_blogs, get_github_stats, ...) ✅ + portfolio context.json / llms.txt endpoints (in progress)
• v3 — "Ask My Portfolio" chat + auto-learning timeline
• v4 — AI personal brief + scheduled refresh

License

MIT © Ayush Kumar