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No. MCP (Model Context Protocol) is not serverless by definition. It specifies how an MCP client communicates with a server, while “serverless” describes where that server runs and how compute is provisioned. A local MCP server normally runs as a client-launched stdio subprocess; a remote server normally exposes the Streamable HTTP transport. That HTTP server can run on Cloud Run, a function platform, Kubernetes, a VM, or a dedicated container.
The practical decision is therefore transport first, hosting second: use stdio for a local desktop or IDE integration, and Streamable HTTP when clients must reach a shared endpoint. Then choose whether that endpoint should be serverless, long-running, or managed.
What an MCP server actually is
An MCP host such as Claude, VS Code, Gemini CLI, or Cursor contains an MCP client. The client connects to an MCP server that publishes tools, prompts, and resources. The server may be on the same computer or on a network service; MCP does not require either location.
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|---|---|---|---|
stdio |
The client launches a subprocess and exchanges newline-delimited JSON-RPC over stdin/stdout; logs belong on stderr. | Developer workstation, desktop application, or local agent runtime | The client owns process startup, shutdown, and local runtime access. |
| Streamable HTTP | An independent server receives JSON-RPC over HTTP POST and may return JSON or an SSE stream. | Cloud service, container, VM, Kubernetes, or serverless platform | You operate networking, authentication, scaling, and observability. |
Because these transports have different lifecycles, a local stdio integration is not made “serverless” by packaging it differently. A remote HTTP implementation can use serverless infrastructure, but that is a deployment choice rather than a protocol property.
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Local stdio: when the client launches your server
With stdio, the MCP client starts your executable as a child process. The server reads one JSON-RPC message per line from standard input and writes only valid JSON-RPC responses to standard output. Diagnostic messages should go to standard error so they do not corrupt the protocol stream.
Best fits
- One developer using an IDE or desktop agent.
- Tools that need local files, credentials, or command-line programs.
- Fast development without DNS, TLS, ingress, or a public identity layer.
Boundaries
- The client machine must have the runtime, dependencies, and executable available.
- There is no shared remote endpoint for a team unless each client installs and launches its own copy.
- Process lifetime follows the host application, so it is a poor fit for an always-available network service.
For a local-only server, bind any auxiliary HTTP listener to 127.0.0.1, not 0.0.0.0. The MCP transport guidance recommends this to reduce exposure to other network hosts.
Streamable HTTP: the remote MCP shape
Streamable HTTP runs your MCP server as an independent process. A client sends JSON-RPC messages with HTTP POST; the server can answer with a JSON object or an event stream (SSE). The client and server negotiate using the transport’s required HTTP headers, and remote deployments should authenticate clients.
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- Origin validation: check every incoming
Originand return HTTP 403 for an invalid value. This is a mandatory DNS-rebinding defense. - Authentication: require an identity mechanism appropriate to your platform, then authorize individual tools rather than treating authentication as blanket permission.
- HTTPS and ingress: terminate TLS at your load balancer or service platform and forward only the MCP route to the application.
- Streaming behavior: configure proxies and timeouts so SSE responses are not buffered or cut off while a tool is running.
A diagnostic request
After your client has completed MCP initialization, you can inspect the tool catalog with a JSON-RPC request like this. Replace the URL, origin, token, and request identifier with values for your service.
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curl -i https://YOUR_MCP_HOST/mcp
-H 'Content-Type: application/json'
-H 'Accept: application/json, text/event-stream'
-H 'Origin: https://YOUR_ALLOWED_ORIGIN'
-H 'Authorization: Bearer YOUR_TOKEN'
--data '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}'A JSON response is the simplest result. An text/event-stream response is also valid; your HTTP client must keep the connection open and parse events until the server signals completion.
Can you deploy an MCP server on serverless infrastructure?
Yes, when the implementation uses Streamable HTTP. Serverless here means that a provider creates and scales the container or function on demand. The same MCP endpoint could instead run continuously on a VM, Kubernetes deployment, or dedicated container without changing the protocol.
Cloud Run
Google’s Cloud Run guidance explicitly supports MCP servers using Streamable HTTP and does not support MCP servers using stdio. Package the HTTP server as a container or deploy from supported Node.js or Python source, configure the listening port supplied by the platform, and protect the resulting HTTPS URL with authentication.
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- Implement an HTTP MCP endpoint and make the port configurable from an environment variable.
- Build a container that starts exactly one web process and writes diagnostics to stderr.
- Deploy the image or source to Cloud Run in the region you need.
- Set ingress and identity controls so only approved MCP clients can call the service.
- Verify Origin checks, authentication, JSON responses, and SSE streaming before connecting an agent.
Function platforms and Lambda-style deployments
A function platform can host an MCP endpoint only if it presents a compatible HTTP interface, preserves streaming behavior where required, and handles authentication and timeouts correctly. The protocol itself does not require a particular provider or function runtime. Validate the provider’s request-duration, response-streaming, concurrency, and cold-start limits before choosing it for long-running tools.
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Managed services
Amazon Bedrock AgentCore requires Streamable HTTP. Its guidance recommends stateless mode for new deployments, while stateful mode exists for capabilities that still depend on session continuity. Google’s remote MCP services add HTTP exposure, discovery, authentication, IAM controls, and optional toolsets for governed environments.
Do MCP servers need persistent sessions?
No. Persistent protocol sessions are optional, and a stateless design is usually easier to scale. The MCP release-candidate announcement dated May 21, 2026 describes a stateless protocol core in which ordinary HTTP infrastructure can route requests without sticky sessions or a shared session store at the protocol layer. It also describes routing hints such as Mcp-Method and Mcp-Name, plus TTL metadata for cacheable list and resource responses.
Stateless does not mean “no state”
Your application may still need conversation state, an OAuth flow, a long-running task, or a cursor. Store that information in a database, cache, object store, or task system and pass an explicit state handle in subsequent calls. AWS describes this pattern as a stateless server backed by external state. The handle must be scoped, authenticated, expiration-limited, and safe to replay or reject.
When session affinity is justified
- A legacy tool keeps non-shareable state in process memory.
- A workflow depends on a live connection that cannot be reconstructed from a durable handle.
- A managed platform’s stateful mode is required for an older capability.
If you choose affinity, document failure behavior: a restarted instance can still lose memory, and a load balancer must route reconnects predictably. Durable state is generally safer than relying on a particular instance.
Choosing a deployment target
| Option | Best fit | Key constraints |
|---|---|---|
| Local stdio process | Desktop IDE or local agent integration | Requires a client-launched process, local runtime, and filesystem access. |
| Cloud Run | Remote Streamable HTTP packaged as a container or source deployment | Does not host stdio MCP servers; configure the HTTP port and authentication. |
| Amazon Bedrock AgentCore | Managed AWS agent workloads | Streamable HTTP is required; stateless mode is the default recommendation, with stateful mode for older session-dependent capabilities. |
| Google Cloud remote MCP services | Governed and discoverable remote tools | Uses HTTP, IAM, authentication, discovery, and optional toolsets. |
Evaluate more than autoscaling
- Cold starts: measure whether startup time fits the client’s request timeout.
- Concurrency: confirm that simultaneous tool calls cannot corrupt in-memory state.
- Streaming: test SSE through every proxy and load balancer.
- Routing: use ordinary round-robin routing for stateless requests; add affinity only when an explicit requirement exists.
- Observability: log request IDs, tool names, latency, status, and authorization decisions without logging secrets or sensitive tool arguments.
- Cost: serverless billing can be attractive for sporadic use, while a continuously busy service may be simpler or cheaper on reserved capacity. Obtain current provider pricing for your region and workload.
Security checklist for remote MCP
- Validate
Originand return 403 when it is not allowed. - Authenticate every remote connection.
- Authorize each tool with IAM or an equivalent policy layer.
- Keep local-only listeners on
127.0.0.1. - Treat tool arguments and outputs as untrusted, security-sensitive data.
- Scan MCP calls and responses when your platform offers a control such as Google Model Armor.
- Define state storage, retention, encryption, and expiration before enabling horizontal scaling.
- Rate-limit expensive tools and set bounded timeouts for outbound requests.
Troubleshooting deployment failures
The client cannot start a stdio server
Check the executable path, file permissions, working directory, runtime version, and environment variables. Run the command manually and send diagnostics to stderr; any logging written to stdout can make JSON-RPC parsing fail.
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Cloud Run returns a port or health-check error
Make the application listen on the port supplied by the platform rather than a hard-coded development port. Confirm that the container starts one HTTP process and that the MCP route is reachable from the service URL.
HTTP calls receive 403
Compare the request’s Origin with your allowlist and verify the authentication identity has permission for the requested tool. Do not disable Origin validation as a shortcut.
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The request times out during a tool call
Inspect cold-start time, upstream API latency, proxy idle timeouts, and the platform’s maximum request duration. For long workflows, return a durable task or state handle and let the client poll or reconnect instead of holding one connection indefinitely.
Streaming works locally but not through the load balancer
Check that the proxy forwards text/event-stream without buffering, keeps the connection alive, and permits the required HTTP methods and headers. Test one hop at a time: container, service URL, then custom domain.
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Frequently Asked Questions
Can one MCP server support both stdio and Streamable HTTP?
Yes, if you provide separate adapters or entry points, but treat them as distinct deployment modes with different lifecycle, security, and configuration requirements.
Is a container automatically a serverless deployment?
No. A container is a packaging unit. It becomes serverless only when a provider runs and scales it through an on-demand serverless model.
What should I load-test first?
Test concurrent tool calls, cold starts, SSE reconnects, authentication checks, and recovery when the backing state store is unavailable.
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