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Personal Context MCP Template

Personal context MCP — template

Serve your personal "how to work with me" manual as an MCP server, so every AI surface you use (Claude Code, chat apps, scheduled agents) loads the same single source of truth about who you are and how you work.

This is a template: the profile sections here are placeholders with writing guidance. Fill them with your own content and you have your own personal-context server. It contains no real profile data and is deliberately independent from the author's actual profile.

The pattern

Whoever works with multiple AI surfaces ends up explaining themselves over and over — and the explanations drift apart. The fix:

  1. One canonical profile: identity, tracks, communication style, hard rules, routines, interfaces, pointers. Markdown, one file per section, in profile/.

  2. A tiny MCP server that serves it: get_profile (everything), get_section (one part), list_sections, plus each section as an MCP resource.

  3. Every surface starts by loading it. Interactive session or headless nightly run: same manual, same rules.

  4. Changing an agreement is one edit in the canon, not a hunt across seven system prompts. Bonus: a periodic drift-check comparing all places where your context lives against this canon.

Two design rules that keep it healthy:

  • Identity only, no live data. Tasks, metrics and budgets live in the systems that own them; the pointers section says where. Operational data in a profile goes stale by lunchtime.

  • Identity first. The section order is deliberate: if an agent reads only one file, it should be identity.md.

Related MCP server: Identity Server

Quick start

Requires Python 3.10+.

pip install -r requirements.txt

# Local, stdio (simplest — Claude Code on the same machine):
claude mcp add my-profile --env MCP_TRANSPORT=stdio -- python -m app.server

# Or as an HTTP server (remote surfaces):
python -m app.server        # http://127.0.0.1:8080/mcp, health at /health

Then fill in the seven files under profile/ — each explains what belongs in it — and ask your agent to get_profile.

If you expose this over HTTP: put real access control in front (an authenticating proxy or tunnel). Your profile is personal by definition; the server itself does no auth, which is why it listens on localhost unless a hosting platform sets PORT (Railway, Render) or you set MCP_HOST=0.0.0.0 yourself (Docker, Fly.io and others that do not set PORT).

requirements.txt pins an exact version on purpose: that lets Dependabot and other scanners match it against known vulnerabilities. Bump it deliberately.

Background

Why this pattern exists and how it behaves in daily use: the write-up in werken-met-cos (Dutch). Built on Anthropic's Model Context Protocol.

License

MIT — see LICENSE.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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  • F
    license
    Not graded
    quality
    D
    maintenance
    A personal MCP server that exposes your profile (bio, skills, projects, work experience) as structured tools for any MCP-compatible AI client, secured with OAuth 2.1 and Dynamic Client Registration.
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  • F
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    A
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    Gives MCP-compatible coding tools a shared, local-first store of your identity, preferences, decisions, and lessons, so agents start from an approved picture of you instead of a blank slate. Everything lives in inspectable local files that you can preview, edit, approve, or override, and that follow you across tools like Claude Code, Codex, Cursor, and Windsurf.
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