MCP Server Deployment

mcp-server-deployment

Run and distribute an MCP server for real users. The failures this skill fixes: in-memory session state that breaks behind a load balancer, servers with no observability into per-tool behavior, big-bang deploys of a protocol surface agents depend on, and "distribution" that ends at a git clone.

Registry/packaging facts verified 2026-07-20 (registry is in preview — re-verify at https://modelcontextprotocol.io/registry/ before publishing).

When NOT to use

• Writing/fixing server code or transports → mcp-server-implementation (incl. SSE→Streamable HTTP migration).
• OAuth/token wiring → mcp-server-auth. Hardening/sandboxing → mcp-server-security. Evals/load-test design → mcp-server-testing.
• Generic web-app deployment with no MCP server involved.

Workflow

1. Choose the delivery modes

2. Architect the remote service stateless

• App nodes hold no cross-request state: sessions/workflow state live in Redis/Postgres keyed by session id (bound to user identity), so any node serves any request behind a plain load balancer. Sticky sessions are a liability, not a strategy — and the 2026-07-28 spec revision removes protocol sessions entirely, so statelessness is also future-proofing.
• Modular monolith first; queue/workers behind slow or fan-out tools to keep p95 tool latency flat; microservices only for concrete org/scale boundaries.
• Serverless caveats: ~30s execution ceilings kill long tool calls (use progress + async patterns from mcp-server-implementation), and long-lived SSE streams need platform support. Managed MCP platforms and gateways (auth/rate-limit/audit termination) are legitimate shortcuts — the auth requirements move there, they don't disappear.

3. Health and rollout

• Liveness = process wedged; readiness = real dependency health (DB, cache, downstream APIs, auth discovery) — not "port open".
• Progressive delivery: canary or blue/green; at each step verify initialize, auth discovery, and one canonical tools/call before shifting more traffic. The per-request nature of Streamable HTTP makes canaries cheap — use them.
• Containers: slim base, non-root, pinned image tags, resource limits.

4. Observability per tool call

• One structured log line + one trace span per tool invocation. Span names like tools.call.<tool_name>; include identity/session as trace attributes and log fields — never as metric labels (cardinality).
• Metrics that matter: per-tool call count, latency percentiles, error rate, isError rate, active streams/sessions, downstream latency, token/cost counters where billable.
• Alert on: sustained 5xx, auth-discovery failures, tool timeout spikes, readiness drops, per-caller cost anomalies. Behavioral anomalies (guardrail blocks, weird session lengths) are the security signal — mcp-server-security consumes these.
• OpenTelemetry end-to-end; logs redact secrets/PII (audit-store rules live in mcp-server-security).

5. Package for local install

MCPB: manifest + server files zipped; supports Node/Python/binary; Claude Desktop bundles a Node runtime; secrets marked "sensitive" are stored in the OS keychain. Keep the manifest's env/config schema minimal and validated at startup. For npm/PyPI: ship an executable entrypoint (npx your-server / uvx your-server), document the exact pinned client-config JSON, and keep tool code per-call self-contained so a misconfigured install can still start and list tools (users see the config error at call time, not a dead server). Server docs ship with the package: every tool documented with at least a few working invocation examples, required permissions/scopes, and rate limits.

6. Publish to the MCP Registry

brew install mcp-publisher            # or the release binary
mcp-publisher init                    # scaffolds server.json
mcp-publisher login github            # verifies the io.github.* namespace
mcp-publisher publish

server.json (schema: static.modelcontextprotocol.io) points at your packages (npm/PyPI/Docker) and/or remotes URL; npm packages must carry a matching mcpName field in package.json for verification; custom-domain namespaces verify via DNS/HTTP challenge. The registry hosts metadata only, is consumed by downstream sub-registries, does not security-review listings, and is in preview — expect possible breaking changes. python3 "${CLAUDE_SKILL_DIR}/scripts/check_server_json.py" server.json gates the manifest before publishing.

7. Version without breaking clients

• Server/package: semver — breaking tool-interface change = major.
• Protocol: date-based revisions negotiated per session; support the current revision plus what your real clients need; send/expect MCP-Protocol-Version correctly (mechanics in mcp-server-implementation).
• Tool surface stability: additive fields over renames; deprecate with a notice window in tool descriptions (agents read them) before removal; schema-snapshot diff in CI (mcp-server-testing) catches accidents.
• Keep a README compatibility note: protocol revisions supported, clients tested, SDK version.

Output spec

A production deployment: stateless nodes with externalized state; readiness gated on real dependencies; canary rollout verifying init/auth/tool-call; per-tool logs+spans+metrics with low-cardinality labels and actionable alerts; local packages (npm/PyPI and/or MCPB) with pinned install docs; registry entry published from a validated server.json under a verified namespace; semver + protocol compatibility note in the README.

Gotchas

• In-memory session state is the #1 horizontal-scaling breaker — externalize before adding replicas, or go stateless and skip sessions entirely.
• Client configs pinned to @latest re-introduce the supply-chain risk your pinning removed — pin in docs and MCPB manifests too.
• Registry preview status is real: entries/data may reset before GA; don't make the registry your only distribution channel.
• Corporate proxies and some LBs buffer or kill long-lived SSE — test the GET stream through the real ingress path, enable heartbeats, and prefer JSON response mode where streams aren't needed.
• A gateway that terminates auth/ratelimits does not exempt the server from validating what reaches it — defense in depth, not delegation.

Pointers

• references/operations.md — reference architecture, probe/rollout/OTel examples, MCPB manifest anatomy, server.json anatomy, gateway pattern, versioning matrix template.
• scripts/check_server_json.py — deterministic registry-manifest gate.