AI agents are good at working with context — when they can actually reach it. The useful notes, saved videos, project decisions, and reference material are often spread across separate apps. MCP is one way to give a compatible agent a defined connection to tools and information instead of pasting the same background into every conversation.
What MCP means
MCP, or Model Context Protocol, is a common way for an AI client to connect to an external server that exposes tools or resources. The protocol does not decide what an agent should be allowed to see. The server still defines its tools, authentication, and permissions.
That distinction matters for personal data. “Connected to an agent” should not automatically mean “the agent can change everything.” A useful connection describes its boundary clearly: whose data it represents, what it can read, what it can do, and how access is revoked.
What personal context looks like in practice
Personal context is more useful than a single pasted note because it can retain the structure around an idea. For example, a saved video might have a source title, transcript, visual evidence, summary, key takeaways, a project mode, ordered tasks, research, and a later conversation. An agent can use that context to answer a question without pretending that the source was just a generic web page.
In ORANO, that context can include:
- Projects and their active, completed, skipped, or archived status.
- Bounded source evidence such as captions, transcripts, visual context, and web references when available.
- Structured understanding, resources, research, learning roadmaps, and ordered tasks.
- Curated memory facts with confidence and freshness signals.
What ORANO MCP can and cannot do
ORANO MCP is a personal, read-focused connection. A compatible client can read the tools that ORANO exposes for the authenticated user: list projects, inspect one project, retrieve explicitly delivered handoffs, search the library, and read curated memory.
It does not give the agent write access to projects, sources, tasks, memory, or account settings. The pending-handoff read is the narrow exception with an explicit delivery acknowledgement: reading a handoff marks that app-triggered delivery as claimed so the same handoff is not delivered repeatedly.
Authentication uses a personal API key with bearer authorization and the orano:read scope. That is different from a public shared knowledge base. The connection is intended to expose one person’s own ORANO context to that person’s chosen agent.
How an agent workflow can use it
- Capture. Save a Reel, video, article, PDF, repository, or other reference in ORANO.
- Understand. Let ORANO extract the useful signal and separate source evidence from generated interpretation.
- Plan. Turn an actionable save into ordered tasks, or keep a non-actionable reference as searchable knowledge.
- Ask. Connect a compatible agent when you want help finding, comparing, extending, or executing from that context.
This is why the handoff is more valuable than simply asking an agent to “summarize my bookmarks.” The agent can start with the structure that was created when the source was understood.
Questions to ask before connecting any personal MCP server
- Is the server personal or shared?
- Does authentication use a scoped key or an unrestricted account session?
- Can the agent write, delete, or change data, or is the connection read-only?
- What evidence is returned with generated summaries?
- How do you revoke a key and delete the underlying account data?
For ORANO, the public MCP overview, agent connection guide, privacy policy, and account-deletion page describe those boundaries. The current hosted flow uses a personal key; a one-click OAuth connection is not being promised until the required OAuth endpoints exist.
Give your chosen agent the useful part of what you have saved.
Explore ORANO MCP