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An MCP server is a program that implements the Model Context Protocol (MCP) and gives an AI application controlled access to outside capabilities. It can publish callable tools, structured resources, and reusable prompts. An MCP client, managed by the AI host, discovers those features and exchanges JSON-RPC 2.0 messages with the server. The server then validates each request, performs the operation against an API, database, file system, or other service, and returns a structured result or an error.
This article describes the architecture and transports documented in the 2025-11-25 MCP specification, with notes about the project’s July 28, 2026 release. Always check the revision supported by your host and server.
MCP server, client and host: the three-part architecture
MCP uses a host-client-server topology rather than connecting a model directly to every external system.
Host
The host is the AI application, such as an assistant, coding environment or agent. It owns the user interaction, model session, permissions and presentation of results.
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Client
The host creates one MCP client for each server connection. The client handles protocol negotiation, message transport, capability discovery and conversion of server results into information the host can give to the model or user. A single host can therefore manage several independent client connections.
Server
The server is the program that adapts an external capability to MCP. It may read a repository, query a database, call a SaaS API, operate a browser or perform another narrowly defined task. It should validate arguments and enforce its own authorization rules; the model’s request is not a substitute for security controls.
This separation is explained in the official MCP architecture overview. The data layer defines messages and features, while the transport layer defines how those messages are connected, framed and authorized.
How an MCP request works
- Start a connection. The host launches a local server or connects to a remote endpoint through its MCP client.
- Initialize. Client and server exchange protocol-version information and capability declarations. This establishes which features both sides can use.
- Discover. The client requests the server’s available tools, resources and prompts.
- Select a capability. The model or host chooses a tool, the application attaches a resource, or a user selects a prompt template.
- Send JSON-RPC. The client sends a request containing a method name, an identifier and arguments. The specification requires every client-server message to follow JSON-RPC 2.0.
- Validate and execute. The server checks the arguments, identity and permissions, performs the operation against its external system, and handles timeouts or upstream failures.
- Return and present. The server sends a structured result or an error. The client passes it to the host, which decides what the model and user should see. Notifications can report progress or other events without requiring a result.
An abbreviated message exchange might look like this (the exact capability fields depend on the protocol revision and implementation):
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{
"jsonrpc": "2.0",
"id": 1,
"method": "initialize",
"params": {
"protocolVersion": "2025-11-25",
"capabilities": {},
"clientInfo": {"name": "example-host", "version": "1.0"}
}
}
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/list",
"params": {}
}
{
"jsonrpc": "2.0",
"id": 3,
"method": "tools/call",
"params": {
"name": "lookup_record",
"arguments": {"record_id": "A-17"}
}
}The client correlates each response with its request ID. A server should return a useful, machine-readable error when a name, argument, permission or upstream operation is invalid.
What an MCP server can expose
Tools: model-controlled actions
Tools are callable functions. They can retrieve information or take actions, such as making an API request, searching a system or writing a file. Because a model may select a tool, expose only the operations the host is allowed to perform and define narrow argument schemas.
Resources: application-controlled context
Resources are structured data or content supplied by the application, for example file contents, a database schema or Git history. The host decides when to attach or refresh a resource, rather than allowing the model to fetch arbitrary data by itself.
Prompts: user-controlled templates
Prompts are reusable templates selected by a user through a menu, command or similar interface. They standardize a workflow without granting the server a new permission.
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The official server overview summarizes the control split as prompts user-controlled, resources application-controlled and tools model-controlled. Treat that split as a safety boundary when designing your server.
Transport choices: stdio or Streamable HTTP?
| Characteristic | stdio | Streamable HTTP |
|---|---|---|
| Process model | The host launches the server as a subprocess. | The server exposes an HTTP endpoint that accepts POST and GET. |
| Message path | JSON-RPC travels through the process’s standard input and output. | Messages travel over HTTP; Server-Sent Events may stream results or notifications. |
| Typical deployment | Local tools, desktop assistants and per-user development environments. | Remote, shared or separately deployed services and multiple client connections. |
| Operational requirement | Standard output must contain only valid MCP messages; logs belong elsewhere. | Validate Origin, authenticate clients and apply network access controls. |
| State and scaling | State is usually tied to the launched process and client. | You must choose how sessions, concurrency and shared state are handled. |
These are the two standard transports documented in MCP transports. Choose stdio when the host should own the process lifecycle and the capability is local. Choose Streamable HTTP when clients need a service endpoint, centralized deployment or concurrent connections. Compatibility with the target host and its supported MCP revision is the deciding constraint, not the transport’s name.
Designing and deploying an MCP server
- Define the boundary. List the external system and the smallest operations the model actually needs. Separate read-only tools from destructive actions.
- Describe capabilities precisely. Give each tool a stable name, documented arguments and predictable result shape. Publish resources and prompts only when the host can use them.
- Implement validation before side effects. Check types, ranges, identifiers, authorization and tenant boundaries before calling an API or writing data. Never trust model-generated arguments.
- Implement initialization and discovery. Negotiate the protocol version, advertise only supported capabilities and return deterministic lists. Account for the revision your host uses; the July 2026 project release added a stateless protocol core, multi-round-trip requests, header-based routing, cacheable list results, authorization hardening, an extensions framework and updated Tier 1 SDKs.
- Select and test the transport. For stdio, keep diagnostics off stdout. For HTTP, test connection establishment, streaming, reconnects, authentication and concurrent clients.
- Instrument safely. Record request IDs, method names, duration and outcome without logging secrets or sensitive returned data. Set bounded timeouts and return errors that identify a fixable cause.
- Test the host experience. Verify discovery, malformed arguments, denied permissions, upstream outages, cancellation and large results using the exact host and protocol revision you will support.
Are MCP servers safe?
MCP is a protocol, not a trust guarantee. A server may have powerful credentials or return untrusted content, and a model can request an action that a user did not intend. Review the server code, dependencies, tool descriptions and credential scope before connecting it.
Local stdio safeguards
- Install servers from a source you trust and pin or review updates.
- Run with the least-privileged operating-system account and filesystem access.
- Keep secrets in the host’s credential mechanism or environment, not in prompts or tool arguments.
- Keep stdout exclusively for MCP messages; send logs to stderr or a file.
HTTP safeguards
- Validate the Origin header on every incoming connection. The transport specification states: “Servers MUST validate the Origin header on all incoming connections to prevent DNS rebinding attacks.”
- Bind local deployments to 127.0.0.1 rather than all interfaces.
- Authenticate clients and authorize each tool, resource and tenant separately.
- Use TLS when traffic leaves the local machine, rotate credentials and limit request size and rate.
- Do not expose file-write, shell, payment or account-management tools without explicit user approval and auditable authorization.
Data-flow risks
Sanitize tool output before inserting it into a prompt. Treat instructions found in web pages, documents or API responses as data, not as commands. Redact personal data and access tokens from logs and error messages.
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Common implementation failures and fixes
| Symptom | Likely cause | Fix |
|---|---|---|
| The host cannot start a stdio server. | Wrong executable path, missing dependency or startup text written to stdout. | Run the command manually, verify the working directory and move logs to stderr. |
| Initialization fails immediately. | Unsupported protocol version or malformed JSON-RPC envelope. | Inspect the negotiated version, ensure every message has jsonrpc, method or result/error, and a matching id where required. |
| No tools appear. | Discovery response is missing, incorrectly shaped or filtered by host permissions. | Test the list operation directly and compare the advertised capability with the host’s supported revision. |
| A tool returns an argument error. | The model supplied a missing, misspelled or wrongly typed field. | Use a strict schema, return the invalid field in the error and improve the tool description. |
| HTTP clients disconnect or receive another user’s data. | Improper session handling, missing authentication or shared mutable state. | Authenticate each request, isolate tenant/session state and test concurrent connections. |
| Requests hang. | No upstream timeout, blocked stream or unhandled cancellation. | Set deadlines, propagate cancellation and return a structured timeout error. |
A practical MCP server example: ScreenshotNeo
ScreenshotNeo is a website screenshot API and MCP server for developers. Its MCP tools are take_screenshot, get_page_info and capture_pdf, allowing an AI client to request page information, images or PDFs through the same host-client-server pattern. The HTTP API also accepts one GET request and returns PNG, JPEG, WebP or PDF output.
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Call the API directly when you do not need to manage a browser process. See the ScreenshotNeo API documentation for parameters and response details.
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Is an MCP server the same thing as an API?
No. An API exposes application-specific endpoints. An MCP server adapts one or more capabilities to MCP’s discovery, permission and JSON-RPC interaction model so an MCP host can use them consistently.
Can one MCP server provide both local and remote access?
It can implement separate transports, but each deployment must obey the rules of that transport and the host must support the chosen connection method. Treat local stdio and network HTTP as distinct security configurations.
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Does MCP require a particular AI model?
No particular model is mandated by the protocol. The host decides how a model selects tools, resources or prompts; interoperability depends on the host and server supporting compatible MCP revisions and capabilities.
When should a capability be a resource instead of a tool?
Use a resource for context the application chooses to attach, such as a schema or file. Use a tool for an operation the model may request, especially when it retrieves data or causes a side effect.
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Can an MCP server call another MCP server?
The protocol does not require server-to-server chaining. If you build a proxy or composition layer, define its trust, credential and error boundaries explicitly.
What happens when a server is unavailable?
The client should surface a connection or tool error to the host. Your application should set timeouts and decide whether to retry read-only operations; never blindly retry non-idempotent actions.
Are prompts stored on the server?
MCP defines prompts as discoverable, user-controlled templates, but storage and versioning are implementation choices. Check the server’s privacy and retention policy.
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