Personal Context MCP

A Markdown-first MCP for Claude Desktop that makes AI memory portable, structured, and user-owned.

What if Claude could wake up inside a memory system you actually own?

personal-context-mcp gives Claude a local folder of Markdown context: durable truths, live priorities, rough notes, and reviewable updates. Claude can search it, build a focused brief before work starts, and capture new observations without turning them into permanent truth by accident.

Instead of trusting an opaque app memory, you get a small personal context layer you can inspect, edit, version, copy, and take with you.

The 10-Second Version

Without this: every important chat starts with you re-explaining who you are, what matters, how you work, and what is currently going on.

With this: Claude can run wake_up_context, read the right local Markdown sections first, and start the task with the context that matters.

Related MCP server: memmd-mcp

In Action

The cool part is the loop: search what matters, wake up with the right bundle, capture rough notes safely, then promote only the pieces that earn trust.

Want the product shape in five minutes? Read the V2 demo walkthrough.

Why Use It

This is most useful if you:

• use Claude heavily

• switch between multiple AI workflows

• want continuity across sessions and projects

• care about user-owned memory instead of product-owned memory lock-in

• want important context to stay reviewable in plain files

What Makes This Different

This project is intentionally opinionated:

• Markdown-first, so the memory layer stays portable and inspectable

• core / dynamic / inbox, so durable truth, working memory, and tentative notes do not get mixed together

• human-reviewable, so important context is visible and editable in plain files

• trust-aware, so rough notes can be captured without pretending they are durable truth

• local by default, so your filled portfolio stays under your control

The point is not "more memory." It is a more inspectable path from rough context to useful context, while keeping durable truth protected.

That is the core bet: the best AI memory is not invisible. It is readable, local, and curated.

V2 Surface

The current V2 surface turns the project from a basic Markdown memory bridge into a fuller personal-context workflow:

• Ranked search: search_memory finds relevant files and sections with transparent ranking reasons.

• Wake-up bundles: wake_up_context builds a small trust-aware bundle before a task starts, so Claude can read the right context first.

• Durable context wrappers: writing_style_context, product_positioning_context, and outbound_framing_context give common high-value prompts explicit entry points.

• Manual ingestion: manual_ingest captures pasted notes, transcript excerpts, and rough summaries into low-trust inbox memory with visible provenance.

• Review and promotion: promote_raw_note, mark_raw_note_status, and link_raw_note_to_proposal let rough notes move toward reusable memory without erasing their trail.

• Safer dynamic maintenance: dynamic files can be appended to, bootstrapped, or updated through exact section/item operations instead of broad rewrites.

The upgrade is not just more tools. It is a tighter loop:

1. Ask Claude what context exists.

2. Search and rank the right Markdown sections.

3. Build a focused read-first bundle.

4. Capture rough notes into low-trust inbox memory.

5. Promote only reviewed context into reusable working memory.

Memory Model

This project uses a simple three-layer memory model:

• core/ Durable truth. Identity, positioning, communication style, operating rules.

• dynamic/ Working memory. Current priorities, active campaigns, recent learnings, message tests, account patterns.

• inbox/ Low-trust notes. Rough observations, partial ideas, and proposed core updates.

This separation is the key design choice: stable truth, evolving memory, and uncertain notes should not collapse into one blob.

Tool Surface

Privacy Boundary

The starter portfolio in this repo is intentionally blank and safe to copy. Your filled personal context portfolio is private data.

Do not commit your filled portfolio to a public repo. The default quickstart name, my-personal-context-portfolio/, is ignored by this repo, but if you choose another name, keep it outside Git or add it to your own .gitignore before filling it in.

See PRIVACY.md for the privacy model.

Requirements

• Claude Desktop with local extensions enabled

• Node.js 20 or newer

• npm

Install

See QUICKSTART.md.

git clone https://github.com/abhinavkalyan10/personal-context-mcp.git
cd personal-context-mcp
npm install
npm run install:extension
npm run prepare:extension

Then install .build/claude-extension/personal-context as an unpacked extension in Claude Desktop.

Repo Structure

.
├── assets/
├── desktop-extension/personal-context/
├── lib/
├── mcp/
├── scripts/
├── starter-personal-context-portfolio/
├── tests/
├── QUICKSTART.md
└── package.json

What This Is Not

This is not magical autonomous memory.

It does not replace:

• judgment

• selective curation

• periodic cleanup

• manual review of durable truth

It also does not add embeddings, a vector database, a knowledge graph, or automatic background writes.

Project Docs

• QUICKSTART.md: install and validation walkthrough

• docs/v2-demo-walkthrough.md: short guided tour of the V2 workflow

• CHANGELOG.md: release history

• PRIVACY.md: privacy model and data boundaries

• SECURITY.md: security policy

Suggested One-Line Description

Personal Context MCP is a portable, Markdown-based memory system for Claude Desktop that separates durable context, working memory, and low-trust notes so AI assistants can stay useful without trapping memory inside one product.

License

MIT