What Is Model Context Protocol (MCP)?
Reviewed by Umar Abbas • CTO & Principal AI Architect
Model Context Protocol (MCP) is an open-source client-server protocol developed by Anthropic that standardizes how artificial intelligence applications expose secure backend tools, internal database resources, and prompt templates to LLMs. MCP replaces custom API code with a unified JSON-RPC 2.0 transport specification.
How Model Context Protocol Works
MCP functions as a client-server architecture. An MCP Host (e.g. an AI agent environment) initializes an MCP Client that establishes a JSON-RPC 2.0 connection to an MCP Server. The server advertises three core capabilities: Tools (executable functions), Resources (read-only data streams), and Prompts (pre-configured instruction templates).
Fintech Payment Gateway MCP Server
In our fintech engineering projects, we deployed a custom Python MCP server exposing ISO 20022 payment transaction records. LLM agents query fraud statuses and tokenized transaction histories through standardized MCP tool calls without raw SQL access.
- Framework: FastMCP Python containerized in Docker.
- Transport: Server-Sent Events (SSE) over TLS with OAuth2 bearer token security.
- Tools Exposed:
get_transaction_status,flag_fraudulent_charge,verify_merchant_kyc.
MCP Protocol vs. Custom REST API Wrappers
| Dimension | Model Context Protocol (MCP) | Custom REST OpenAPI Wrappers |
|---|---|---|
| Standardization | Unified open specification (JSON-RPC 2.0) | Proprietary per-application glue code |
| Tool Discovery | Dynamic protocol capability negotiation | Static text parsing of OpenAPI YAML files |
| Interoperability | One server works across Claude, Cursor & agents | Requires rewrite for every new AI client environment |
| Streaming Support | Native progress notification streams | Requires custom Server-Sent Events engineering |
When to Adopt Model Context Protocol
- You are building enterprise AI agents that query internal databases and tools.
- You want to expose internal microservices to multiple AI tools without rewriting integration code.
- Your security architecture demands explicit separation of LLM context from database credentials.
- Your application is a simple static text generator with no tool calls.
- You are building a monolithic single-process Python application without out-of-process boundaries.
How Esaholic Engineers MCP Servers
We build enterprise MCP server microservices connecting legacy databases to autonomous LLM agent swarms.
Frequently Asked Questions
Who created the Model Context Protocol standard?↓
Anthropic open-sourced the Model Context Protocol standard in November 2024 to establish an open industry specification for AI tool integration.
How does an MCP server communicate with an MCP client application?↓
MCP uses JSON-RPC 2.0 messages framed over standard input/output (stdio for local tools) or Server-Sent Events (SSE over HTTP/TLS for cloud services).
What is the primary architectural benefit of deploying MCP servers?↓
MCP decouples tool implementation from the LLM runtime: a single MCP server can be accessed by Claude Desktop, Cursor IDE, or custom agent runners without code changes.
How does MCP prevent unauthorized database modification tool calls?↓
MCP servers expose capability declarations, restricting client authorization scopes to read-only tool tools and requiring explicit JSON Schema parameter validation.