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Build Mcpb

OrganizationPopular
anthropics
build-mcpb

This skill should be used when the user wants to "package an MCP server", "bundle an MCP", "make an MCPB", "ship a local MCP server", "distribute a local MCP", discusses ".mcpb files", mentions bundling a Node or Python runtime with their MCP server, or needs an MCP server that interacts with the local filesystem, desktop apps, or OS and must be installable without the user having Node/Python set up.

Overview

Publisheranthropics
Repositoryclaude-plugins-official
Skill namebuild-mcpb
Stars
36.4K
Forks
4.1K
Bundled files
2
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by anthropics on GitHub. Read the source before you install it.

Installation

Install the Build Mcpb AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anthropics/claude-plugins-official.git /tmp/claude-plugins-official
mkdir -p .claude/skills
cp -r /tmp/claude-plugins-official/plugins/mcp-server-dev/skills/build-mcpb .claude/skills/build-mcpb
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Build Mcpb in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Build Mcpb on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Build Mcpb is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Build an MCPB (Bundled Local MCP Server)

MCPB is a local MCP server packaged with its runtime. The user installs one file; it runs without needing Node, Python, or any toolchain on their machine. It's the sanctioned way to distribute local MCP servers.

MCPB is the secondary distribution path. Anthropic recommends remote MCP servers for directory listing — see https://claude.com/docs/connectors/building/what-to-build.

Use MCPB when the server must run on the user's machine — reading local files, driving a desktop app, talking to localhost services, OS-level APIs. If your server only hits cloud APIs, you almost certainly want a remote HTTP server instead (see build-mcp-server). Don't pay the MCPB packaging tax for something that could be a URL.


What an MCPB bundle contains

my-server.mcpb              (zip archive)
├── manifest.json           ← identity, entry point, config schema, compatibility
├── server/                 ← your MCP server code
│   ├── index.js
│   └── node_modules/       ← bundled dependencies (or vendored)
└── icon.png

The host reads manifest.json, launches server.mcp_config.command as a stdio MCP server, and pipes messages. From your code's perspective it's identical to a local stdio server — the only difference is packaging.


Manifest

json
{
  "$schema": "https://raw.githubusercontent.com/anthropics/mcpb/main/schemas/mcpb-manifest-v0.4.schema.json",
  "manifest_version": "0.4",
  "name": "local-files",
  "version": "0.1.0",
  "description": "Read, search, and watch files on the local filesystem.",
  "author": { "name": "Your Name" },
  "server": {
    "type": "node",
    "entry_point": "server/index.js",
    "mcp_config": {
      "command": "node",
      "args": ["${__dirname}/server/index.js"],
      "env": {
        "ROOT_DIR": "${user_config.rootDir}"
      }
    }
  },
  "user_config": {
    "rootDir": {
      "type": "directory",
      "title": "Root directory",
      "description": "Directory to expose. Defaults to ~/Documents.",
      "default": "${HOME}/Documents",
      "required": true
    }
  },
  "compatibility": {
    "claude_desktop": ">=1.0.0",
    "platforms": ["darwin", "win32", "linux"]
  }
}

server.typenode, python, or binary. Informational; the actual launch comes from mcp_config.

server.mcp_config — the literal command/args/env to spawn. Use ${__dirname} for bundle-relative paths and ${user_config.<key>} to substitute install-time config. There's no auto-prefix — the env var names your server reads are exactly what you put in env.

user_config — install-time settings surfaced in the host's UI. type: "directory" renders a native folder picker. sensitive: true stores in OS keychain. See references/manifest-schema.md for all fields.


Server code: same as local stdio

The server itself is a standard stdio MCP server. Nothing MCPB-specific in the tool logic.

typescript
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
import { readFile, readdir } from "node:fs/promises";
import { join } from "node:path";
import { homedir } from "node:os";

// ROOT_DIR comes from what you put in manifest's server.mcp_config.env — no auto-prefix
const ROOT = (process.env.ROOT_DIR ?? join(homedir(), "Documents"));

const server = new McpServer({ name: "local-files", version: "0.1.0" });

server.registerTool(
  "list_files",
  {
    description: "List files in a directory under the configured root.",
    inputSchema: { path: z.string().default(".") },
    annotations: { readOnlyHint: true },
  },
  async ({ path }) => {
    const entries = await readdir(join(ROOT, path), { withFileTypes: true });
    const list = entries.map(e => ({ name: e.name, dir: e.isDirectory() }));
    return { content: [{ type: "text", text: JSON.stringify(list, null, 2) }] };
  },
);

server.registerTool(
  "read_file",
  {
    description: "Read a file's contents. Path is relative to the configured root.",
    inputSchema: { path: z.string() },
    annotations: { readOnlyHint: true },
  },
  async ({ path }) => {
    const text = await readFile(join(ROOT, path), "utf8");
    return { content: [{ type: "text", text }] };
  },
);

const transport = new StdioServerTransport();
await server.connect(transport);

Sandboxing is entirely your job. There is no manifest-level sandbox — the process runs with full user privileges. Validate paths, refuse to escape ROOT, allowlist spawns. See references/local-security.md.

Before hardcoding ROOT from a config env var, check if the host supports roots/list — the spec-native way to get user-approved directories. See references/local-security.md for the pattern.


Build pipeline

Node

bash
npm install
npx esbuild src/index.ts --bundle --platform=node --outfile=server/index.js
# or: copy node_modules wholesale if native deps resist bundling
npx @anthropic-ai/mcpb pack

mcpb pack zips the directory and validates manifest.json against the schema.

Python

bash
pip install -t server/vendor -r requirements.txt
npx @anthropic-ai/mcpb pack

Vendor dependencies into a subdirectory and prepend it to sys.path in your entry script. Native extensions (numpy, etc.) must be built for each target platform — avoid native deps if you can.


MCPB has no sandbox — security is on you

Unlike mobile app stores, MCPB does NOT enforce permissions. The manifest has no permissions block — the server runs with full user privileges. references/local-security.md is mandatory reading, not optional. Every path must be validated, every spawn must be allowlisted, because nothing stops you at the platform level.

If you came here expecting filesystem/network scoping from the manifest: it doesn't exist. Build it yourself in tool handlers.

If your server's only job is hitting a cloud API, stop — that's a remote server wearing an MCPB costume. The user gains nothing from running it locally, and you're taking on local-security burden for no reason.


MCPB + UI widgets

MCPB servers can serve UI resources exactly like remote MCP apps — the widget mechanism is transport-agnostic. A local file picker that browses the actual disk, a dialog that controls a native app, etc.

Widget authoring is covered in the build-mcp-app skill; it works the same here. The only difference is where the server runs.


Testing

bash
# Interactive manifest creation (first time)
npx @anthropic-ai/mcpb init

# Run the server directly over stdio, poke it with the inspector
npx @modelcontextprotocol/inspector node server/index.js

# Validate manifest against schema, then pack
npx @anthropic-ai/mcpb validate
npx @anthropic-ai/mcpb pack

# Sign for distribution
npx @anthropic-ai/mcpb sign dist/local-files.mcpb

# Install: drag the .mcpb file onto Claude Desktop

Test on a machine without your dev toolchain before shipping. "Works on my machine" failures in MCPB almost always trace to a dependency that wasn't actually bundled.


Reference files

  • references/manifest-schema.md — full manifest.json field reference
  • references/local-security.md — path traversal, sandboxing, least privilege

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Build Mcpb AI skill do?

This skill should be used when the user wants to "package an MCP server", "bundle an MCP", "make an MCPB", "ship a local MCP server", "distribute a local MCP", discusses ".mcpb files", mentions bundling a Node or Python runtime with their MCP server, or needs an MCP server that interacts with the local filesystem, desktop apps, or OS and must be installable without the user having Node/Python set up.

Why use Build Mcpb on TypingMind?

Because you install it once and use it with any model. Build Mcpb is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Build Mcpb in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/claude-plugins-official/tree/main/plugins/mcp-server-dev/skills/build-mcpb. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Build Mcpb?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Build Mcpb?

As many as you like. As long as a model supports skills, you can use Build Mcpb with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Build Mcpb AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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