What is VCP?
A protocol for portable, adaptive, live context across AI and services.
Every new AI service starts from zero, and to be understood you have to overshare. VCP is an open protocol that sends the what and keeps the why. You declare your preferences, constraints, and current state once. Services and agents that speak VCP receive short flags, plain enough for you to read, that they can honor without learning your story.
Three properties that matter
Today your context is stuck inside each service, the same in every situation, and frozen at whatever you last entered. VCP makes it portable, adaptive, and live.
Portability
Define your context once. Compatible services can read the fields they support, so you repeat yourself less.
Adaptation
Context can switch with your situation, from work mode at the office to personal mode at home, when the integration activates the matching profile.
Liveness
Tell a service you are tired or pressed for time, and where it supports live updates, the tone and depth of its answers can shift with you.
How it works
You declare your context. VCP encodes it as structured data. Services read supported flags and adapt without seeing private reasons behind them.
You set context
Define your goals, constraints, and current state. Mark what is shareable and what stays private.
VCP encodes it
Private circumstances become categorical flags. "Thin walls" becomes noise_restricted. The flag travels. Your story stays home.
Services adapt
Apps and services that speak VCP read the flags they support and adjust. They can update as your state changes.
The protocol ships as a specification, not a promise. VCP defines how context is written, carried, and checked; it cannot make a service obey it. Only a service that implements VCP reads the flags, and that service decides what to do with them. A signature shows which trusted key signed a bundle and that it arrived unchanged, not that anyone followed it. And a flag says far less than your story, but not nothing: consent, storage, and what a service infers from it remain the job of the application that holds your data.
Six protocol layers.
Three context tiers
VCP carries context in three tiers that change at different speeds: stable rules (the constitutional tier), shifting situations (the situational tier), and moment-to-moment state (the personal tier).
Constitutional rules
What the AI should and should not do.
Personas, safety boundaries, rulesets, adherence levels
Changes rarely
Situational context
Where, when, who, what occasion.
Morning vs. evening, alone vs. with children, home vs. work
Changes per session
Personal state
How you are right now.
Cognitive state, emotional tone, energy level, perceived urgency, body signals
Changes moment to moment
Not a magic mirror
You declare your context, and the AI adapts to what you share. If a system infers anything, VCP requires it to say so, show its confidence, and let you correct it.
Works with MCP
VCP is designed to work with the Model Context Protocol (MCP). MCP is the delivery channel. VCP is the structured content it carries.
Delivery
Connects AI agents to tools and data sources. The plumbing.
Policy
Encodes values, context, and constitutional rules. The meaning.
The Python SDK includes an MCP server, so an MCP-compatible agent can call VCP tools to validate a token, parse a CSM-1 code, and encode the current context. In browsers that support WebMCP, the SDK's WebMCP package registers VCP tools on the page itself.
See it in action
These are six of the site's nine demos, each a scripted simulation. Three show portability, adaptation, and liveness; three take VCP into energy negotiation, school governance, and medical diagnosis.
Gentian's guitar journey
One learner carries context across three apps
Campion's corporate training
Work and personal profiles for one person
Marta's responsibility journey
Her current state shapes the guidance she gets
Ren's energy cooperative
AI agents carry values into an energy negotiation
Noor's school district
A school district's AI homework rules, enforced as application hooks
Dr. Hana's diagnostic tool
Confidence labels on each AI claim