What is the MCP protocol? Standardization trends that enterprise AI agents must understand in 2026
Break the problem
Have you ever encountered this situation?
The company bought an AI customer service system, only to find that it can only accept LINE, but cannot access website chat, Email, or Discord. **
Then the boss said: “Then buy another website for chatting.”
“But the data in the two systems are not connected…”
“That’s called manufacturer integration.”
“The manufacturer said it would take two months…”
This is the current situation of the AI Agent industry: there are many tools, but no one talks to anyone. **
After MCP (Model Context Protocol) comes out, this problem has a chance to be solved.
What is MCP? Why it could be the USB-C of AI
Imagine a world…
Before there was USB-C:
- Lightning for iPhone
- Micro-USB for Android
- Laptops use all kinds of weird connectors
You need to buy adapter cables, you need to bring several cables, you need to confirm the direction of the connectors - and then at a critical moment you find out, “Ah, this cable is from the previous phone.”
The problem MCP wants to solve is the same as USB-C: **Unified interface so that any AI Agent can “plug and play” any tool. **
How MCP works
Traditional AI Agent serial connection method (most are still used today):
LLM → 寫程式串 API → 硬生生接在一起Question:
- Each LLM needs to be written once for each application
- If you change one place, you will need to retest everything.
- There is no standard, change the model and start all over again
MCP way:
LLM ←→ MCP Client ←→ MCP Server ←→ 各種工具
↑
（標準化的「轉接頭」）**Any AI that supports MCP can directly call any tool that supports MCP - like any USB device plugged into a USB slot. **
Currently supports MCP tools
The good news is: the ecosystem is growing rapidly.
| Category | MCP Support Tools |
|---|---|
| Development tools | Claude Code, Cursor, VS Code (expected) |
| Messaging platform | SLAck, Discord, LINE (in progress) |
| Database | PostgreSQL, MySQL, Notion, Google Drive |
| E-commerce | Shopify, WooCommerce |
| Enterprise Tools | Salesforce, HubSpot |
According to Anthropic 2026 Q1 data, 500+ MCP Servers are available.
Why should companies care about MCP?
Current pain points
When most companies introduce AI Agents, they will encounter the “island problem”:
- Information is not connected: CRM customer information and customer service system are two different worlds
- Each application needs to be re-stringed: If you want to be a LINE customer service, you have to string it once, and if you are a website customer service you have to string it again.
- High maintenance costs: API updates, changing suppliers, everything has to be done again
Changes brought about by MCP
| Dimensions | Without MCP | With MCP |
|---|---|---|
| Integration time | 2-4 weeks/each time | 1-2 days/each time |
| Maintenance cost | High (each integration is independent) | Low (standardized interface) |
| Changing suppliers | Painful (re-string everything) | Easy (only change the client side) |
| Ecosystem Compatibility | Closed | Open |
**To put it simply: MCP allows AI Agent to change from “customized integration” to “assembled development”. **
Who is best suited to import now?
MCP is not a panacea. The following companies are most worthy of investment:
- Multi-channel customer service: LINE + official website + Email + Facebook - each one needs to be connected
- Multi-system operation: CRM + ERP + inventory + accounting - data must be connected
- Fast-growing new innovation: If you use tool A today, you may change to tool B tomorrow. MCP makes it easier for you to replace it.
If your application is very simple (only one LINE account), the value of MCP may not be obvious.
3 practical suggestions for enterprises to introduce MCP
1. First verify “MCP is really needed here”
MCP is not required everywhere. Assessment method:
| Question | If the answer is Yes, consider MCP |
|---|---|
| Do you have more than 3 tools/systems that require string AI? | ✅ |
| Might these tools be replaced in the future? | ✅ |
| Will integration require cross-teams (RD/PM/Marketing)? | ✅ |
| Only string 1-2 tools, will it not change in the short term? | ❌ (Direct string API is faster) |
2. Choose the right development framework
Currently the most mature MCP development portfolio:
- Anthropic Claude + Claude Code = The most complete MCP ecosystem
- OpenAI + OpenAI Agents SDK = supports MCP but later than Claude
- OpenClaw = Our platform with built-in MCP support
If you are just starting to build an AI Agent, it is recommended to choose Claude Code or OpenClaw, as MCP has the most complete integration.
3. Take safety precautions
MCP’s “plug and play” feature is a double-edged sword——
Risk: If an MCP Server is hacked, the attacker can directly collude with your AI to do anything.
Protective Measures:
- Only install trusted MCP Servers (do not npm install those from unknown sources) -Set MCP permission scope (do not give admin permissions)
- Regular audit logs
- Added “Human Confirmation” level for important operations
Trend Forecast for 2026: Will MCP Become Standard?
My opinion: Yes, but it will take time
Reason for optimism:
- Major manufacturers (Anthropic, OpenAI, Google) have expressed support
- The developer ecosystem is growing rapidly
- Enterprises do have the need to “go to silos”
Challenge:
- The old system may not support MCP, and the transformation cost is high
- The standard is still evolving (version 1.0 is expected in 2026 Q3)
- Some major manufacturers may choose to “play their own game”
What should companies do now?
- Pay attention, don’t be anxious: The MCP ecosystem is still growing. Let’s first observe which servers are mature.
- For new projects, give priority to tools with MCP: For example, choose a CRM with MCP support instead of writing the integration yourself.
- Build internal AI capabilities: MCP or not, you need someone who understands the AI Agent architecture
FAQ
Q1: What is the difference between MCP and API?
A: API is a method that “allows two programs to speak”, and MCP is a protocol that “allows AI Agents to standardize any tool.” Simply put: MCP is a wrapped API that is easier, safer, and more standard.
Q2: What impact does MCP have on developers?
A: If you are developing AI applications, MCP allows you to write 70% less integration code. Once an MCP Server is written, all Agents that support MCP can use it.
Q3: What should I do if the AI tool I am using does not support MCP?
A: No need to rush to change. You can first evaluate:
- Will this tool be upgraded in the short term? (Ask the manufacturer)
- Are existing integrations stable? (If you don’t change it often, just maintain it first)
- Is there any need for expansion in the future? (If so, consider alternatives that support MCP)
Next step
Want to know what kind of AI Agent architecture is suitable for your company?
- Use ROI Calculator — Calculate the benefits of AI Agent integration
- Reserve a free consultation — Help you evaluate whether MCP is needed now