How to Deliver Personal Context to AI Tools
MCP, API, and export - how context reaches the tools you use
You've built your personal context. Now what?
Getting it into the tools you actually use is where most people stall. They paste it manually into every new chat, or set it up in one tool and forget the others. Result: one tool knows who you are. The rest don't.
There are four delivery methods. Each has different trade-offs. The right one depends on what tools you're using and how much you want to automate.
What "delivering context" actually means
When an AI tool starts a session, it has no idea who you are. Delivering context means getting your Identity, Profile, Mind, and Environment in front of the model before it responds to your first message.
Two fundamentally different ways this happens:
- Pull - the tool requests your context from an external source automatically at session start
- Push - you provide it manually: paste a file, upload a doc, write it into a system prompt
Pull (MCP, API) is automatic and stays current. Push (exports, manual paste) requires action every time, and the context is only as fresh as the last time you updated it.
Method 1: MCP (recommended)
Model Context Protocol - an open standard, released by Anthropic in 2024, now adopted across the industry. It lets AI tools pull structured data from external servers at session start.
How it works:
- Your context vault is exposed as an MCP server
- You add a one-line config to your AI tool
- Every session, the tool pulls your current context automatically - no pasting, no re-prompting
Works with: Claude Desktop, Claude Code, Cursor, and any other MCP-compatible agent or IDE.
What you control: access is per-app and per-layer. A coding assistant gets Identity and Profile, not Mind. Revoke any tool instantly.
Set it up once. Every session in every connected tool starts with fresh, accurate context.
When MCP isn't the answer
MCP requires a client that supports it. Most browser-based tools and many specialized apps don't yet. For those, use one of the methods below.
Method 2: Structured file export
Your context vault exported as Markdown files. Paste or upload directly into any AI tool.
How it works:
- Export your context as
.mdfiles (identity.md, profile.md, or one combined file) - Paste into a system prompt, Claude Project, ChatGPT custom instruction, or the tool's context window
- The tool has your context for that session
Works anywhere that accepts text input - ChatGPT, Perplexity, Notion AI, local LLM interfaces. No MCP required.
The trade-off: exports are a snapshot. New project, role change, shifted priorities - the file doesn't update automatically. Re-export and re-paste.
Best for tools without MCP support, one-off sessions, and sharing context with a collaborator.
Method 3: OpenAI function calling
A developer-facing option. Your context vault is exposed as a callable function in the OpenAI API. The model calls it when relevant and gets structured data back.
Instead of front-loading context into every prompt, context gets delivered on demand.
Best for developers building custom AI apps who want personal context without depending on MCP. Requires development work - not a user-facing path.
Method 4: REST API
Direct programmatic access to your context vault via HTTP. Authenticate, call the endpoint, get structured data. Any system that can make an API call can read your context.
Best for custom integrations with internal tools, automated workflows, or anything that needs context injected at a specific step. The most flexible option - also the most setup.
How to choose
| Method | Setup | Stays current | No MCP needed | Best for |
|---|---|---|---|---|
| MCP | Low | ✅ | ❌ | Daily use in Claude, Cursor |
| File export | None | ❌ manual | ✅ | ChatGPT, any tool |
| Function calling | High | ✅ | ✅ | Custom AI apps |
| REST API | High | ✅ | ✅ | Custom integrations |
Most people: MCP where it's supported, exports everywhere else.
Developers: MCP or function calling depending on the integration pattern, REST for custom workflows.
Permissions across all methods
Every delivery method uses the same permission model. Each connection gets a scoped token - access only to the layers you authorized. Revoke any connection and access is gone immediately.
MCP connections are per-app. Exports are explicit - you choose what to include. API tokens are scoped at issuance. The context is yours across all paths.
Getting started
Using Claude Desktop or Cursor? MCP is the setup worth doing first. → How to Load Your Personal Context into Claude and Cursor via MCP
Haven't built your context yet? Start there. → How to Build Personal Context for AI
Set up your context vault with Unabyss
