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MCP does not define an AI model, replace an API gateway, or make connected tools safe automatically. It defines how an AI host, its MCP clients, and MCP servers exchange messages and discover capabilities.
What is Model Context Protocol?
MCP standardizes the connection between an AI application and external systems such as:
- Local files and folders
- Databases
- Business applications and SaaS platforms
- REST APIs and internal services
- Development tools and code repositories
- Reusable prompts and agent workflows
Without a common protocol, each AI application needs a custom connector for each service. MCP provides a shared interface. An AI assistant that supports MCP can connect to many MCP servers, while a server can work with multiple compatible hosts.
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Anthropic introduced MCP publicly on November 25, 2024. The project was later donated to the Linux Foundation’s Agentic AI Foundation, co-founded by Anthropic, Block, and OpenAI.
MCP is frequently described as “USB-C for AI.” The comparison means that MCP aims to provide a common connection standard; it does not mean MCP uses USB or shares USB’s technical design. MCP messages use JSON-RPC 2.0.
How MCP works
MCP separates the AI application from the external service:
- The host is the AI application or agent runtime, such as an assistant or coding environment.
- The host creates an MCP client for each server connection.
- The MCP server exposes tools, resources, or prompts.
- The host decides how those capabilities are shown to the model and user.
A server does not inherently contain or control the language model. It provides a standard way to expose capabilities. The host remains responsible for model interaction, user experience, permissions, and—depending on the application—approval before an action is executed.
| Component | Role |
|---|---|
| Host | The AI application or agent runtime. |
| Client | The host-side component that maintains communication with one MCP server. |
| Server | The program or service that exposes data, actions, or reusable prompt templates. |
One host can use several clients to connect to several servers. For example, an AI coding application might connect to one server for a project directory, another for GitHub, and a third for a company issue tracker.
MCP server primitives
MCP defines three main server-side primitives. Their control models matter:
| Primitive | Control model | What it provides | Example |
|---|---|---|---|
| Tools | Model-controlled | Executable functions that can read information or perform actions. | Run a database query, create a ticket, or call an API. |
| Resources | Application-controlled | Structured content or data supplied by the host. | A document, file, schema, or record collection. |
| Prompts | User-controlled | Reusable prompt templates or workflows selected by the user. | A code-review template or incident-summary workflow. |
“Model-controlled” does not mean the model must be allowed to perform an operation without approval. A host can require confirmation, restrict certain tools, or prevent a tool from being made available at all.
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MCP also defines client-side features including roots, sampling, and elicitation. Optional features such as logging, pagination, completion, and subscriptions are supported according to the capabilities advertised by the implementation.
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MCP messages follow JSON-RPC 2.0. Requests have an integer or string ID and receive a response. Notifications do not have IDs and do not receive responses. A request ID of null is not valid.
MCP uses JSON Schema to describe and validate structured arguments and results. In the current specification, schemas without an explicit $schema value default to JSON Schema 2020-12. Implementations may support other dialects, but should document them.
The current stable specification listed by the official MCP documentation is 2026-07-28. It changes an important assumption found in older MCP tutorials: the modern protocol core is stateless.
Modern versus legacy MCP
| Protocol era | Main behavior |
|---|---|
2026-07-28 and later |
Stateless core; requests carry relevant protocol and client information. Modern Streamable HTTP does not use Mcp-Session-Id. |
2025-11-25 and earlier |
Legacy initialization handshake and connection-oriented assumptions. |
| Dual-era implementation | Supports both modern and legacy clients or transports. |
Code written from an older tutorial may expect an initialize/initialized exchange or a session header. A modern client and legacy server can therefore fail before a tool is ever called. Check the protocol version supported by both sides rather than copying session-related configuration blindly.
MCP transports
The two standard transports are stdio and Streamable HTTP.
stdio
With stdio, the host launches the MCP server as a local subprocess. The two programs exchange newline-delimited JSON-RPC messages through standard input and output.
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The server must write only protocol messages to stdout. Diagnostic output belongs on stderr. A single startup banner can corrupt the stream:
// Unsafe for an MCP stdio server
console.log("Server starting...");
// Use stderr for diagnostics instead
console.error("Server starting...");This is one of the most common reasons a local server reports malformed JSON, disconnects immediately, or appears not to initialize.
Because a local server runs with the privileges available to the host application, installing one is similar to installing any other executable. Review its source or publisher, restrict its filesystem and network access, and avoid running it with administrator or root privileges unless there is a clear requirement.
Streamable HTTP
Streamable HTTP uses a single MCP endpoint that supports POST and GET, such as:
https://example.com/mcpThe server may use Server-Sent Events for streaming, but a permanently open bidirectional session is not required. In the 2026-07-28 design, requests include headers such as:
MCP-Protocol-Version: 2026-07-28
Mcp-Method: tools/call
Mcp-Name: search_documentsThe method and name in the headers must agree with the JSON-RPC request body. A reverse proxy that drops or rewrites these headers can cause otherwise valid requests to fail.
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HTTP servers must validate the Origin header and return 403 Forbidden for an invalid origin. A local HTTP server should normally bind to 127.0.0.1, not 0.0.0.0, unless wider exposure is deliberate and protected. This reduces the risk of DNS-rebinding attacks.
The older HTTP+SSE transport appears in legacy documentation. It may still be needed for compatibility with older clients, but Streamable HTTP is the current standard design.
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Authorization and security
Authorization is optional at the MCP protocol level, but a network-accessible server needs normal authentication and authorization controls. HTTP implementations that use authorization should follow the MCP authorization specification.
- Send access tokens in
Authorization: Bearer <token>. - Do not put access tokens in URL query strings.
- Validate the token’s issuer, audience, expiry, and other relevant claims.
- Do not accept a client token and blindly forward it to a downstream API. Token passthrough is explicitly forbidden.
- Do not treat an MCP session ID as an authentication mechanism.
- Limit each tool to the smallest practical set of permissions.
- Require human confirmation for destructive or externally visible actions.
MCP does not make a server trustworthy. Tool descriptions, schemas, returned data, resource contents, icons, and prompt text should all be treated as untrusted input. A tool result can contain prompt-injection instructions designed to influence the model.
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Remote authorization discovery also needs care. A malicious server could advertise an authorization URL pointing to a loopback address, private network, link-local address, or cloud metadata endpoint. Clients performing discovery should validate HTTPS, redirects, DNS results, and reserved IP ranges to reduce SSRF and DNS-rebinding risks.
Common MCP errors and fixes
| Symptom | Likely cause | What to check |
|---|---|---|
| Malformed JSON or immediate stdio disconnect | Logs or a startup banner were written to stdout. | Move diagnostics to stderr and inspect the raw stdout stream. |
| Initialization or session error | Client and server expect different protocol eras. | Compare supported versions and whether the implementation expects an initialization handshake or session header. |
| HTTP request rejected by a gateway | Missing or changed MCP headers. | Preserve MCP-Protocol-Version, Mcp-Method, and Mcp-Name; compare headers with the JSON body. |
| Tool call fails with a capability error | The server requested an undeclared client feature. | Check advertised capabilities such as sampling, elicitation, or roots. Modern implementations may return error code -32021. |
| Local HTTP connection returns 403 | Invalid or unexpected Origin header. | Review Origin validation and bind the service only to the intended interface. |
| Tool works once but loses context later | Application state was inferred from connection reuse. | Pass a conversation, job, or resource identifier explicitly in each relevant request. |
Debugging an MCP server
The official MCP Inspector is the quickest way to test a server independently of a full AI application. It can connect to stdio and Streamable HTTP servers, list resources and prompts, invoke tools, and display notifications.
Run it with:
npx @modelcontextprotocol/inspector <command>For a stdio server, verify that:
- The command can run successfully outside the AI application.
- Environment variables and working directories are correct.
- Only newline-delimited MCP messages appear on stdout.
- Logs and stack traces appear on stderr.
- Tool schemas accept the arguments the client sends.
For an HTTP server, inspect the endpoint URL, HTTP status, Origin, authorization header, MCP version, method and name headers, JSON-RPC body, and any SSE response. Test the server directly before adding a reverse proxy or load balancer.
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Claude Desktop logs are stored on macOS under ~/Library/Logs/Claude and on Windows under %APPDATA%Claudelogs. After changing server code or configuration, fully restart the client. Closing a window may not terminate the background client process.
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What MCP is not
- Not an AI model: MCP does not generate responses or choose a model.
- Not an API gateway: It does not replace routing, rate limiting, identity providers, network policy, or application authorization.
- Not a security boundary: It does not automatically make tools, prompts, or results safe.
- Not limited to Claude: Multiple AI assistants and development tools support MCP, although their supported features and protocol versions differ.
- Not automatically a conversation protocol: Modern MCP is stateless at its core. State that spans requests should be represented by explicit IDs or handles.
FAQ
What does MCP stand for?
MCP stands for Model Context Protocol. It is an open protocol for connecting AI applications to external data sources, tools, APIs, and reusable workflows.
Is MCP only for Claude?
No. MCP was introduced by Anthropic, but the protocol is designed for multiple AI assistants and development tools. Compatibility depends on the host’s supported protocol version and features.
What is the difference between an MCP host, client, and server?
The host is the AI application, the client is the host-side connection component, and the server exposes tools, resources, or prompts. One host can create multiple clients for multiple servers.
Is it safe to install any MCP server?
No. A local MCP server can read files, run commands, access credentials, or make network requests with the host’s privileges. Install servers only from trusted sources, restrict permissions, sandbox them where possible, and require approval for risky actions.
Which MCP transport should I use?
Use stdio for a local server launched by the AI application. Use Streamable HTTP for a remotely accessible or separately hosted service. HTTP+SSE is an older transport retained mainly for legacy compatibility.
How do I debug an MCP server?
Use the MCP Inspector with npx @modelcontextprotocol/inspector <command>. For stdio, make sure stdout contains only JSON-RPC messages and send logs to stderr. For HTTP, inspect status codes, Origin, authorization, MCP headers, and the JSON-RPC body.
The Bottom Line
MCP gives AI applications a consistent way to discover and use external tools and data, but it is an integration protocol—not a complete security, identity, or workflow system. Start with the correct transport, confirm the client and server use compatible protocol versions, keep stdio output clean, preserve HTTP headers, and apply least privilege and human approval to every consequential tool.
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