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Every technical leader sees the same future: agents everywhere. Agents in the product improve the customer experience. Internal agents eliminate manual work, boost productivity, and save costs. The potential is enormous.

But potential and reality diverge at the infrastructure layer.

As companies go from having one agent to many, they see the integration problem get worse with every agent shipped. They end up in "integration hell" with a tangled mess of custom connectors between the LLM and data sources that aren't secure, reusable, or maintainable.

There's a better way. Companies like Faire, Block, and Cisco have figured out that they can build a standardized MCP tool layer that enables them to scale their agent fleet securely.

The Integration Tax

Let’s walk through how this plays out at a typical company, an SMB banking platform we'll call "Acme Co."

Acme starts with a customer support agent to handle basic questions: password resets, account status, check processing.

Agent #1 (Customer Support) needs:

Customer profile data
Account balance lookups
Transaction history
Knowledge base access
Email/SMS notifications

Four integrations. Straightforward.

Then they build Agent #2 for collections to automatically contact customers about late payments. This is where the cracks start to show.

Agent #2 (Collections) needs:

Customer profile data (duplicate from Agent #1, but needs payment preferences)
Account balances (duplicate from Agent #1)
Payment history
Payment arrangement creation
Email/SMS notifications (duplicate from Agent #1, but different templates and timing)
Twilio for phone calls
Interaction logging

Now they're maintaining 13 integrations, with overlap in functionality and potentially distinct auth.

Agent #3 monitors for fraud patterns. Agent #4 handles business loan inquiries. Agent #5 investigates failed ACH payments.

By Agent #5, you have 25+ custom integrations. Each slightly different. Each needing maintenance when APIs change. Each requiring its own security review. Each slowing down your next agent.

The MCP Tool Layer

The Model Context Protocol solves this by introducing a standardized tool layer between your agents and your services.

Instead of custom code for each agent-service pair, you build MCP servers once. Every agent accesses them through a standard protocol.

Why This Architecture Wins

1. Build once, use everywhere

Your account lookup server works for customer support, collections, credit analysis, and fraud detection. Write it once, secure it once, maintain it once. Every new agent gets the benefit of battle-tested infrastructure.

2. Ship agents in days, not weeks

New agents become a question of orchestration, not integration. Your team focuses on the business logic that differentiates your agents while reusing proven tools. Agent #10 ships faster than agent #3.

3. Adapt without breaking changes

Need to switch from Twilio to a different provider? Update one MCP server. All 15 agents that use it keep working. Infrastructure changes stop cascading through your entire agent fleet.

4. Add semantic intelligence

MCP adds a semantic layer that allows agents to decide which tool to use when. Instead of calling tools in a fixed sequence, agents can reason dynamically about the task at hand, choose the right MCP tools, and compose them intelligently.

5. Enable non-technical builders

Product managers and operations teams can compose agents from existing MCP tools without writing integration code. The same way Zapier democratized automation, MCP democratizes agent building within your organization.

6. Security and governance at the tool layer

Authentication, rate limiting, audit logs, and access control live in one place—your MCP gateway. Not scattered across 25+ custom integrations, each with slightly different security models. Compliance becomes tractable.

How Leading Companies are Approaching It

In the overwhelming sea of AI information, it can be helpful to look to companies that have gone down this path.

Faire built an orchestration layer called Fairey that uses MCP to pull context into agentic systems. Their engineering team can now build AI-powered workflows without writing custom integrations for every service. Read their approach →

Cisco deployed Circuit, an internal AI system handling 100K+ employee interactions daily. Rather than each AI feature needing custom connectors, they built a unified tool layer that any agent can access. See the results →

Getting Started

If you’re ready to scale data connectors:

Read the MCP specification at modelcontextprotocol.io
Identify your highest-impact services.
Set up a simple MCP infrastructure layer.
Expand incrementally as new agents come online.

Want to Build an MCP Tool Layer?