An MCP server exposes tools and data to AI agents through the Model Context Protocol, and calls other systems using its own credentials.
{
"servers": {
"crm": {
"command": "npx",
"args": ["-y", "crm-mcp-server"],
"env": { "CRM_TOKEN": "••••••" }
}
}
}From a security point of view an MCP server is a non-human identity. Whatever credentials sit behind its tools, such as API keys, OAuth tokens or service accounts, define what an agent using it can reach. A server shared by several agents concentrates their access.
See MCP server access and our MCP security checklist.
An MCP server exposes tools and data to AI agents through the Model Context Protocol, and calls other systems using its own credentials.
The parts that make it up, in an environment with AI agents.
The server exposes tools and data an agent can call.
Each tool calls other systems with the server’s own keys or tokens.
Several agents can call the same server and inherit its access.
Whatever those credentials reach is reachable by every agent using it.
A real path shape, drawn the way the Elmoz security graph shows it.
Short answers about MCP server.
In practice yes. It calls other systems with credentials such as API keys, OAuth tokens or service accounts, and those credentials define what it can reach.
Local servers usually run on the user’s machine over stdio and use credentials from local config. Remote servers are reached over HTTP and handle authentication themselves, often with OAuth.
Scope the credentials behind each tool, avoid long-lived static keys, give shared servers their own identity per agent where possible and review which agents can call it.
Terms that belong to the same picture.
Book a demo and we walk through the access paths in an environment like yours.