RAG & Agents · Field note 007
MCP servers and the future integration layer
AI systems produce better outcomes when they can reach trustworthy context. Historically, every integration meant a custom build. Standardized interfaces like the Model Context Protocol are starting to change that math — and introducing a new governance surface along with it.
Beyond retrieval
The opportunity here extends past feeding documents into a model. Standardized interaction models open up discovery, controlled access, governance, and monitoring as shared concerns instead of per-integration afterthoughts.
Discovery
Agents can find what context and tools are available without a bespoke integration per system.
Controlled access
Permissions travel with the connection instead of being reimplemented by every client.
Governance
A standard interface gives security and compliance one place to look, not dozens.
Monitoring
Usage and failures become visible across every integration, not just the ones someone remembered to instrument.
The other side of the coin
Every new integration opportunity also introduces security and compliance concerns that didn't exist when each connection was custom-built and narrowly scoped. A standard protocol makes it easier to connect an agent to real systems — which means it also makes it easier to connect an agent to real systems without anyone noticing until an audit.
The long-term challenge is balancing that openness with control. Organizations that solve it well unlock real productivity gains; organizations that don't end up with an agent sprawl problem that looks a lot like shadow IT, just faster and less visible.
Registry plus gateway, not either/or
- AI client or agent
- MCP / tool gateway
- Approved registry + policy enforcement
- Audit & telemetry
- Enterprise APIs, knowledge, workflow systems
A registry helps teams discover what tools are available. A gateway helps enforce policy on what they're allowed to do with them. Mature organizations need both — discovery without enforcement creates risk, and enforcement without discovery just creates friction that pushes people toward unmanaged workarounds.
This is a rerun of a lesson enterprises already learned with APIs: unmanaged APIs create sprawl, managed APIs create reuse, security, and visibility. AI tool protocols are on the same path, just compressed into a much shorter timeline.
Questions worth asking
Before the next server gets connected
Who owns integration governance once connections stop being one-off engineering projects and start being self-service? What does the approval model look like when a new capability can be added in an afternoon instead of a quarter?