frontmcp-deployment

frontmcp-deployment is a skill for Claude Code, Codex from agentfront/frontmcp. It costs 210 tokens per session (4,656 once invoked), scanned A, original, Apache-2.0.

A guide for choosing where and how to build and deploy a FrontMCP server. FrontMCP is a TypeScript framework for making services that AI clients can call.

In plain words
What is it for?
Use it when comparing Node, Vercel, AWS Lambda, Cloudflare, command-line, browser, SDK, serverless, or desktop-package targets, or when moving between them.
Why use it?
It helps you match the server or build format to your infrastructure instead of choosing a deployment option blindly.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/agentfront/frontmcp/frontmcp-deployment
Any agent
npx skills add agentfront/frontmcp --skill frontmcp-deployment
Clone the repo
git clone --depth 1 https://github.com/agentfront/frontmcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for frontmcp-deployment

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentfront/frontmcp/frontmcp-deployment.svg)](https://agentmods.dev/skills/agentfront/frontmcp/frontmcp-deployment)
Your own site
<a href="https://agentmods.dev/skills/agentfront/frontmcp/frontmcp-deployment"><img src="https://agentmods.dev/badge/skills/agentfront/frontmcp/frontmcp-deployment.svg" alt="Measured on agentmods" height="20"></a>
Per session 210 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,656 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00210 $0.04656
Opus 5 $0.00105 $0.02328
Sonnet 5 $0.00042 $0.00931
Haiku 4.5 $0.00021 $0.00466

Measured 4d ago against content hash 1afcb19327e3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

frontmcp-deployment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

libs/skills/catalog/frontmcp-deployment/SKILL.md · 260 lines

How it starts

The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.

FrontMCP Deployment Router

Entry point for deploying and building FrontMCP servers. This skill helps you choose the right deployment target or build format based on your infrastructure requirements.

When to Use This Skill

Must Use

  • Choosing between deployment targets (Node vs Vercel vs Lambda vs Cloudflare) for a new project
  • Deciding on a build format (server vs CLI vs browser vs SDK) for distribution
  • Planning infrastructure and need to understand trade-offs between deployment options

Recommended

  • Comparing serverless platforms for cost, cold-start, and feature support
  • Understanding which transport protocol and storage provider each target requires
  • Migrating from one deployment target to another

Skip When

  • You already know your deployment target (go directly to deploy-to-node, deploy-to-vercel, etc.)
  • You need to configure server settings, not deploy (see frontmcp-config)
  • You need to build components, not ship them (see frontmcp-development)

Decision: Use this skill when you need to figure out WHERE to deploy. Open the matching reference under references/ directly when you already know.

Prerequisites

  • A working FrontMCP server with at least one @App and one @Tool (see frontmcp-development)
  • Server configuration completed (see frontmcp-config)
  • Tests passing locally (see frontmcp-testing)

Steps

  1. Review the Scenario Routing Table and Target Comparison below to choose a deployment target
  2. Run frontmcp build --target <target> to produce the build output
  3. Follow the specific deployment reference (e.g., references/deploy-to-node.md, references/deploy-to-vercel.md) for platform instructions
  4. Verify with the Post-Deployment checklist at the end of this skill

Scenario Routing Table

Scenario Reference Description
Long-running server on VPS, Docker, or bare metal deploy-to-node Node.js with stdio or HTTP transport, PM2/Docker for process management
Serverless with zero config and Vercel KV deploy-to-vercel Vercel Functions with Streamable HTTP, Vercel KV for storage
AWS serverless with API Gateway deploy-to-lambda Lambda + API Gateway with Streamable HTTP, DynamoDB or ElastiCache
Edge computing with global distribution deploy-to-cloudflare Cloudflare Workers with KV or Durable Objects for storage
Hosted FrontMCP (v1.3 skills-only model) deploy-to-cloudflare-skills-only Cloudflare Worker as the MCP control plane; OpenAPI is capability inventory; agent uses 4 meta-tools + AgentScript; hot-reload via GitHub Action
Author frontmcp.deploy.yaml deploy-manifest-yaml v1 schema reference: runtime, server, specs, skills, tags, classification, bindings, signing, auth, secrets, environments
Standalone executable binary for distribution build-for-cli Single-binary CLI with stdio transport, embedded storage
Run MCP in a web browser build-for-browser Browser-compatible bundle with in-memory transport
Embed MCP into an existing Node.js application build-for-sdk Library build for programmatic usage without standalone server
Write a Dockerfile for Node.js deployment deploy-to-node-dockerfile Dockerfile configuration for Node.js deployment
Configure Vercel-specific settings (vercel.json) deploy-to-vercel-config Vercel-specific configuration (vercel.json)
Connect MCP clients (Claude, Cursor, VS Code) mcp-client-integration Configure .mcp.json for stdio, HTTP, or Unix socket transport
Serve or consume MCP protocol 2026-07-28 protocol-versions Stateless requests, server/discover, mirrored headers, MRTR, tasks extension, and the McpStatelessClient

Read the full file on GitHub · 260 lines

Files

What ships with it

42 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 260 lines · 210 tokens per session scan A 1afcb19327e3

Subscribe to this mod's changes

frontmcp-deployment is a skill published in the GitHub repository agentfront/frontmcp (146 stars, last pushed 2d ago), licensed Apache-2.0. It adds 210 tokens to every session and 4,656 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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