MCP standardizes the connection between AI and enterprise tools
Anthropic launched the Model Context Protocol (MCP) in late 2024, and the protocol is seeing dazzling adoption in 2025. MCP defines an open standard to connect any LLM to any tool: database, API, CRM, ERP, file system. More than 2,000 MCP servers are available open-source on GitHub. Google, Microsoft and Salesforce have announced their support. MCP could become for AI what the HTTP protocol was for the web.
Opportunities for businesses
MCP solves the number one problem of AI in the enterprise: integration with existing systems. Three concrete use cases are emerging.
Autonomous AI agents
An AI agent can now query your CRM, check stock in the ERP and send a quote by email, all in a single conversation. MCP orchestrates these interactions without specific code.
Plug-and-play integration
No more need to develop a custom connector for each tool. One MCP server for Salesforce, one for PostgreSQL, one for Google Workspace: the AI accesses everything through a unified interface.
Real-time contextual AI
The LLM has up-to-date business context (customer data, stock, calendar) without anyone having to copy-paste information into the prompt. Response accuracy up by 35%.
Risks to anticipate
Security and data access
An MCP server gives the LLM direct access to your systems. Without granular access control, a poorly worded prompt could expose sensitive data. Implement role-based permissions and an audit log on every MCP call.
Ecosystem maturity
MCP is young: the specification is less than a year old. Some community servers lack tests and documentation. Favor official servers (Anthropic, Google) or audited ones, and plan a validation phase before production.
Our recommendations
Identify your 3 priority integrations
List the tools your teams use most in conjunction with AI (CRM, document base, ERP). Check that an MCP server exists for each one on the official registry or GitHub.
Deploy a POC with Claude Desktop
Claude Desktop natively supports MCP. Connect an MCP server to your database or your CRM and test it on a concrete use case (e.g. a sales assistant). Budget: 2,000 to 5,000 EUR for a 1-week POC.
Secure before industrializing
Before scaling the deployment, put in place an authorization layer (OAuth 2.0), a rate limiter and an audit log. Define roles and permissions for each MCP server.
Key takeaways
Frequently asked questions
Is MCP an open standard?
Yes. Anthropic published the specification under the MIT license. Any company can implement MCP servers free of charge. Google, Microsoft and several independent vendors have already announced their support, which makes it a de facto standard for AI-to-tool integration.
Do you need to change your infrastructure to adopt MCP?
No. MCP works as an intermediary layer between your AI and your existing tools. You deploy a lightweight MCP server in front of each tool (database, API, CRM) without modifying the tool itself. Deploying a connector takes 1 to 3 days.
Is MCP compatible with LLMs other than Claude?
Yes. Although created by Anthropic, MCP is model-agnostic. Implementations already exist for GPT-4, Mistral and Llama. The ecosystem of open-source MCP servers on GitHub exceeds 2,000 projects in June 2025.
MCP tech sheet
Model Context Protocol (Anthropic, 2024)
Open protocol (MIT license) that standardizes communication between LLMs and external tools. Client-server architecture with JSON-RPC transport over stdio or HTTP/SSE.
Pricing
Comparison
| Criterion | MCP | Function Calling (OpenAI) | LangChain Tools |
|---|---|---|---|
| Open standard | Yes (MIT) | No | Yes |
| Model-agnostic | Yes | No (OpenAI) | Yes |
| Connector ecosystem | 2,000+ | GPT plugins | 500+ |
| Native security | In progress | Basic | Variable |