The MCP ecosystem is at an inflection point. What started as a protocol for connecting AI assistants to external tools has become the default integration layer for a generation of AI-powered engineering tools — Claude, Cursor, Windsurf, GitHub Copilot. Thousands of MCP servers exist. Tens of thousands of developers have installed them.
Almost none of them have thought about what happens when this goes to production.
The Individual Problem Is Solved
For a solo developer, MCP is close to perfect. You find a server, copy a JSON snippet, paste it into your config file, restart your AI client, and you have a new capability. GitHub integration, database access, Slack messaging, web search — all available in natural language. The friction is low enough that exploration is easy.
The MCP ecosystem solved the individual problem well.
The Team Problem Is Not
The moment a second person joins, the model breaks.
Authentication. You have a workspace token. You share it with your team. Now everyone has the same access to every tool. You cannot differentiate between what Alice is allowed to do and what Bob is allowed to do. You cannot revoke Bob's access without rotating the token — which breaks every AI client on the team simultaneously.
Deployment. Most MCP servers run as local stdio processes via npx. They exist only on the machine where they were installed. They cannot be shared across a team. They cannot be put behind a gateway. They cannot be monitored or audited. When a developer leaves, their MCP servers leave with them.
Visibility. When something goes wrong — when a production database gets queried unexpectedly, when a CI/CD pipeline is triggered by an agent, when sensitive data appears in a context where it should not — you cannot answer the most basic post-incident question: "which agent called which tool, and when?" There is no log. There is no audit trail. There is no answer.
Quality. 7,500+ MCP servers exist. GitHub stars measure historical interest, not current health. A server with 3,000 stars may not have had a commit in 18 months. There is no quality signal. There is no trust layer.
Why This Matters Now
AI agents are moving toward production infrastructure. They are not just answering questions — they are writing code, querying databases, triggering deployments, sending messages. The tools they use via MCP are real tools with real access to real systems.
The governance problem is not theoretical. It is the same problem that made API keys dangerous before OAuth, that made server access chaotic before centralised identity providers, that made network access ungovernable before Zero Trust. Every time a powerful capability becomes accessible to teams, governance follows — because it has to.
MCP is at the API key moment. The capability exists. The governance does not.
What Governance for MCP Looks Like
A governance layer for MCP needs to answer four questions consistently:
1. Who is using which tools?
Every tool call must be attributable to a specific person. Not "the workspace called something" — "Alice called the database query tool." Member-level attribution requires per-member tokens and protocol-level logging.
2. What is each person allowed to do?
Access control must operate at the tool level, not the workspace level. The security engineer should not have the same MCP permissions as the junior developer. Tool allowlists per member enforce least privilege at the protocol layer.
3. How do you revoke access instantly?
When someone leaves the team, their access must be gone in seconds. Without touching anyone else's configuration. Without rotating credentials that break the whole team. Per-member tokens make this possible.
4. Where do the servers run?
Local stdio processes are ungovernable by design. MCP servers need to run in isolated environments with defined lifecycles — deployable, monitorable, and terminatable without touching developer machines.
The Category That Does Not Exist Yet
Enterprise MCP governance is not a product category yet. It will be.
The same pattern has played out in every previous infrastructure layer. API management was chaos before control planes emerged. Identity was chaos before centralised providers. Network access was chaos before Zero Trust made it manageable.
MCP is the next layer. The governance problem is structural, not optional. And the window to define this category is open now — before the major platforms build their own solutions, before the ecosystem consolidates, before the standard emerges.
The teams that govern MCP today will not be scrambling to retrofit security into production deployments tomorrow.
Ricardo Rodrigues is the founder of MCPNest.io and a Platform Engineer at a large financial institution in Portugal. MCPNest.io is the enterprise governance layer for MCP servers — Gateway, per-member access control, hosted infrastructure, and audit logging.
mcpnest.io
Top comments (1)
You’ve hit on the exact pressure point where early MCP adoption will struggle in the enterprise: we’ve solved for interoperability, but we haven’t yet standardized on intent.
The 'fenceless' nature of MCP is exactly why a Sovereign System approach is necessary. In this model, the MCP server isn't just a data provider; it acts as a Governance Gate. We have to move from 'Reactive Enforcement' (catching a bad prompt after it’s already been processed) to a 'Proactive Negotiation' layer that sits between the agent and the resource.
This isn't just a safety requirement; it’s a Fiscal Architecture necessity. Without a governance gate, companies pay an 'Infrastructure Tax' in three ways:
Redundant Discovery: Agents burning expensive cloud tokens to repeatedly 'discover' tools they already have access to.
Hallucination Labor: The sunk cost of high-value engineers debugging agentic errors caused by ungrounded tool calls.
Unmanaged Burn: Giving an agent a 'corporate credit card' (API access) with no spending limit or audit trail.
By implementing a 'Sieve-and-Sign' pattern, where a local-first gateway inspects the tool call before it reaches the reasoning engine, we can optimize the Unit Economics of Intelligence. We turn a black-box expense into a predictable, high-yield infrastructure asset.
I’m curious: do you see this governance living within the individual MCP servers, or as a centralized 'Intelligent Sieve' that proxies all tool traffic?