What is MCP?
MCP (Model Context Protocol) is an open protocol, introduced by Anthropic in November 2024, that gives AI applications a standard way to connect to tools, data sources and business systems. In December 2025 Anthropic donated MCP to the Agentic AI Foundation (AAIF) under the Linux Foundation, so the protocol is now developed under a neutral foundation. Instead of writing a separate integration for every model and every system, you expose a system once as an MCP server, and any AI application that supports MCP can use it.
Definition
MCP (Model Context Protocol) is an open protocol, introduced by Anthropic in November 2024, that gives AI applications a standard way to connect to tools, data sources and business systems.
How does MCP work?
MCP uses a client-server architecture. The AI application (the client) connects to one or more MCP servers. Each server represents a system such as a CRM, a file store or a database. A server can offer three kinds of things: tools the model can call (create a record, look up an order), resources the model can read (documents, tables) and reusable prompt templates. The model decides which tool is needed, the client passes the call to the server and returns the result to the model.
When should you use MCP?
When an AI agent needs to act in company systems, and when more than one AI application is expected to access the same system. For a single model and a single integration, a direct API call may be enough. As the number of systems grows, a standard protocol reduces maintenance and simplifies agentic AI architectures.
MCP for systems in Türkiye
Writing an MCP server for a Turkish ERP such as Logo, Mikro or Netsis, an e-invoice integrator or a marketplace seller panel opens that system to different AI tools in one go. When a server touches personal data, limit from the outset which tool returns which fields, in line with GDPR and KVKK, Türkiye’s data protection law. Access rules and logging should be documented as part of your AI governance.
Related terms
- AI agentAn AI agent is software that uses a language model to decide which steps to take towards a goal and then carries out those steps with tools such as APIs, databases and email.
- Agentic AIAgentic AI is an approach in which AI systems do more than generate answers: they set sub-goals, plan, use tools and carry out multi-step work with limited human intervention.
- LLM (Large Language Model)An LLM (large language model) is an AI model trained on very large amounts of text that answers questions, summarises, translates and writes by predicting what text should come next.
- AI governanceAI governance is the set of policies, roles and processes that determine how an organisation selects, uses, oversees and manages the risks of its AI systems.
Frequently asked questions
Does MCP only work with Anthropic Claude?
No. MCP is an open protocol, and many AI applications and developer tools beyond Anthropic's have added MCP support. Check the current support of the client you plan to use.
Is it safe to run an MCP server?
If it is designed properly, yes. The server should expose only the operations that are needed, use authentication and authorisation, log every call and require confirmation for write actions. MCP servers from untrusted sources should be reviewed carefully.
Let’s talk about your transformation
Tell us which work repeats every week. We will tell you honestly whether it is worth automating.
How we start
- A free first callWe pin down the problem and the goal together.
- A 2-week discovery sprintWe look at the data, the process and the tools, and decide where to start.
- A written proposalScope, architecture and timeline, in writing.