Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Offline MCP server for planning structured project specs — validate, render, and checklist tools.
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"draftlytic": {
"command": "npx",
"args": [
"-y",
"draftlytic-mcp"
]
}
}
}Run this in your terminal
claude mcp add draftlytic -- npx -y draftlytic-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"draftlytic": {
"command": "npx",
"args": [
"-y",
"draftlytic-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"draftlytic": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"draftlytic-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account rbsoftwaresystems, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.4.1) reached the registry 4 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Claude Checkpoint MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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An MCP server that turns a rough project idea into a structured spec — right inside Claude Code, Cursor, or any MCP-compatible editor. No API key, no account, no network calls. It runs entirely on your machine and hands your editor's model a schema to write into, a checklist of what to ask about, a validator that catches gaps before you start coding, and a renderer that turns the result into a clean Markdown PRD.
This exists because "vibe coding" from a one-line prompt tends to produce a plausible-looking app that's missing half the decisions you actually needed to make — what's in scope for v1, what the data model looks like, what "done" means for a feature. draftlytic-mcp doesn't generate any of that for you; it structures the conversation so your model asks the right questions, then checks its own homework before you start building.
claude mcp add draftlytic -- npx -y draftlytic-mcp
Add to .cursor/mcp.json in your project (or the global ~/.cursor/mcp.json):
{
"mcpServers": { "draftlytic": { "command": "npx", "args": ["-y", "draftlytic-mcp"] } } }
Most MCP hosts read a generic mcp.json with the same shape:
{
"mcpServers": { "draftlytic": { "command": "npx", "args": ["-y", "draftlytic-mcp"] } } }
Once connected, ask your editor's model something like:
Use the plan_project prompt for "a habit tracker that reminds me by text message"
It'll walk through spec_checklist with you (platform, tech stack, audience, features, competitors, revenue, constraints, data model, notifications, external services, design & UX — a handful of concrete questions per category, many offered as click-to-pick single/multi-select choices rather than blank prompts, with a free-text escape always available), draft a spec, run it through validate_spec, fix what comes back, and hand you a rendered PRD in Markdown you can drop straight into a coding-agent prompt, a SPEC.md, or a GitHub issue.
You can also call the tools directly if you already have a spec drafted (by hand, or from another source) and just want it checked and rendered.
| Tool | Input | What it does |
|---|---|---|
validate_spec | spec (JSON object) | Zod-validates the spec and returns structured issues: errors for missing/empty required sections, placeholder text (TBD, lorem ipsum, fixme, etc.), and features without a priority — plus non-blocking quality hints like "no acceptance criteria on your must-haves" or "no non_goals listed". |
render_prd | spec (JSON object) | Renders a validated spec into deterministic Markdown: title, overview, target audience, platforms, tech stack, features grouped by priority with acceptance-criteria checklists, screens & navigation, data model tables, constraints, and non-goals. Refuses to render (returns an error) if the spec has structural errors. |
spec_checklist | — | Returns the planning checklist grouped by category, each with 2-4 concrete questions. Each question is { prompt, options?, multiSelect? } — questions with options are meant to be shown as selectable single/multi-choice answers (with a free-text escape), open ones stay free-text. |
open_in_draftlytic | spec (JSON object, optional) or idea (string) | Builds a link that opens your idea in the full Draftlytic app with the brief pre-filled — its guided AI question flow, richer generation, an editable spec editor, and PRD export live there. Compresses a spec (even a partial one) into a starting brief, or takes a plain-text idea. Builds the URL locally; sends nothing anywhere. |
Plus one prompt:
| Prompt | Args | What it does |
|---|---|---|
plan_project | idea (string) | Instructs the model to interview the user with spec_checklist, draft a spec, validate and fix it in a loop, then render the final PRD. |
{
name: string overview: string target_audience: string platforms: string[] tech_stack: string[] features: Array<{ title: string description: string priority: "must-have" | "nice-to-have" | "future" acceptance_criteria?: string[] }> screens?: Array<{ name: string; purpose: string }> data_model?: Array<{ entity: string fields: Array<{ name: string; type: string; notes?: string }> }> constraints?: string[] non_goals?: string[] revenue_model?: string }
validate_spec and spec_checklist are heuristics, not a substitute for actually knowing what you're building. A spec that passes validation can still be a bad plan.TBD/lorem ipsum/fixme-style filler, not "this description is vague but technically real words."draftlytic-mcp is the offline sibling of draftlytic.com — the full editor adds AI generation, logo drafts, scan-for-gaps, and GitHub push.