An MCP server for Packkit — let AI agents (Claude Desktop, Cursor, Windsurf, …) scaffold modern npm packages, CLIs, HTTP services, and front-end apps as a native tool.
packkit_schema — every option, preset, and alias as JSON (call first to learn the interface).
packkit_preview — the files a config would generate, without writing anything.
packkit_scaffold — generate a project to disk (optional git init + install).
Related MCP server: npm-run-mcp-server
Add to your MCP client config (e.g. Claude Desktop's claude_desktop_config.json):
{
"mcpServers": {
"packkit": {
"command": "npx",
"args": ["-y", "packkit-mcp"]
}
}
}Then ask your agent things like "scaffold a React component library called ui with Storybook" or "preview a Hono service named api".
Also listed on the official MCP registry as io.github.PackkitJS/packkit-mcp and on Glama.
Publishing a new version touches npm, the official MCP registry and Glama — see RELEASING.md.
MIT © DanMat
Show the project structure a config would produce — the full file tree and stack summary — without writing anything. Use this to check the layout before committing to it, and to show the user what they are about to get. Cheap and side-effect free, so prefer it over scaffolding to a throwaway directory to see what happens.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Package name | |
| preset | No | A preset or alias (e.g. ts-lib, react-lib, node-service, rlib) | |
| options | No | Any options from packkit_schema (e.g. { "framework": "vue", "target": ["library"] }) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description bears full responsibility. It clearly states 'without writing anything' and 'side-effect free', indicating a non-destructive, read-only operation. However, it could explicitly confirm that it only reads data and does not modify state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. The first sentence front-loads the core purpose and behavior ('Show the project structure...without writing anything'). The second sentence provides usage guidance. Every phrase adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 3 parameters (1 required), no output schema, and no annotations. The description sufficiently covers the tool's function (preview file tree and stack summary), its non-destructive nature, and when to use it. No major gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage for parameters is 100%, so the baseline is 3. The description does not add extra context beyond the schema (e.g., data types, constraints, or examples). It mentions 'name', 'preset', 'options' but no additional semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('Show', 'check', 'prefer it over scaffolding') and clearly states the tool produces a full file tree and stack summary without writing anything. It uniquely identifies the tool as a dry-run preview, distinguishing it from scaffolding.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('to check layout before committing', 'show the user what they are about to get') and when not to ('prefer it over scaffolding to a throwaway directory'). Also highlights that it is cheap and side-effect free, guiding preference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate a project to disk. Writes files under / (or ./), optionally runs git init, installs dependencies, and creates the GitHub repository. Call packkit_schema first if you have not already — picking the preset by guess is how projects end up the wrong shape. If the target directory already has files in it (an existing clone, for instance), pass merge: true rather than failing.
| Name | Required | Description | Default |
|---|---|---|---|
| git | No | git init + initial commit (default false) | |
| name | Yes | Package name (also the folder name) | |
| merge | No | Scaffold into a non-empty directory. Existing files are never overwritten — colliding ones are skipped and reported. Use this when the target is an already-cloned repo. | |
| github | No | Create the repository on GitHub and push to it, using the `gh` CLI. Requires git. Private unless "public" is set. | |
| preset | No | A preset or alias | |
| public | No | When creating the repository, make it public (default: private) | |
| install | No | Install dependencies (default false) | |
| options | No | Any options from packkit_schema | |
| directory | No | Parent directory to create the project in (default: current working directory) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses file placement, optional side effects (git init, dependency install, GitHub repo creation), and the failure/skip behavior for existing directories. Since no annotations are provided, the description carries the burden and handles it well, though it omits GitHub auth requirements (which appear in schema).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each informative: purpose, file path/effects, schema prerequisite, and merge guidance. No fluff, front-loaded with the action, and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 9-parameter tool with nested objects and no output schema, the description covers the essential behavior: where files go, optional actions, the schema precondition, and the merge edge case. It does not describe return values or detailed error handling, but those are less critical and the schema covers parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 9 parameters have schema descriptions, so baseline is 3. The description adds context about the directory/name relationship and merge semantics, but these are largely covered in the schema. No substantial per-parameter insight beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States the core action clearly: "Generate a project to disk." and specifies output location and optional side effects (git init, install, GitHub repo). This distinguishes it from sibling tools like packkit_schema (which provides presets) and packkit_preview (likely a dry-run).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call packkit_schema first, with a rationale ("picking the preset by guess is how projects end up the wrong shape"). Also provides specific guidance for non-empty directories: pass merge: true rather than failing. This is strong when-to-use guidance relative to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
START HERE. Returns every Packkit option, preset, and shortcut alias as JSON. Call this before scaffolding so you pick a preset that matches what the user actually wants — presets range from single libraries to CLIs, HTTP services, SPAs, and full-stack monorepos, and guessing without reading them is the main cause of scaffolding the wrong shape.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly states the tool returns JSON and describes the content, but it doesn't explicitly state whether the operation is read-only or has side effects. However, given the tool's name ('schema') and that it 'returns' data, it is clearly non-destructive. The description adds useful context about the range of presets and the consequence of not using it, which goes beyond a basic description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence but remains highly readable. It starts with 'START HERE' to immediately signal priority, then states the action, the timing, and the rationale. Every word earns its place, with no fluff. It is well-structured and memorable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters and no output schema, the description provides sufficient context: what it does, why to use it, when to use it, and the variety of options it returns. It also differentiates itself from siblings by positioning itself as the prerequisite step. The description is complete for its intended purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is nothing to explain. The baseline for 0-parameter tools is 4. The description does not mention parameters, which is fine because none exist. It adequately communicates the tool's function without needing to cover parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Returns every Packkit option, preset, and shortcut alias as JSON.' It uses a specific verb ('returns') and a specific resource ('every Packkit option, preset, and shortcut alias'). The 'START HERE' directive and comparison with siblings (preview, scaffold) distinguish it as the discovery/entry-point tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Call this before scaffolding' and explains why: 'so you pick a preset that matches what the user actually wants' and warns that 'guessing without reading them is the main cause of scaffolding the wrong shape.' This gives clear when-to-use guidance and implies that for scaffolding-related tasks, this tool should precede others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Only one tool exists, so there is no possibility of confusion or overlap.
With a single tool, naming consistency is not an issue; the name follows a clear verb_noun pattern.
A single tool for a project scaffolding server is too few; expected more tools like create, scaffold, or config to cover the domain.
The server only provides a preview operation, lacking any scaffolding or writing capabilities, leaving significant gaps in the tool surface.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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