specpack

Audit and write CLAUDE.md / AGENTS.md / Cursor rules; generate full build specs for new projects.

Should I use this

Quality & Safety

A
Description quality
100%
Schema completeness
71%
Naming quality
96%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~826Tokens (tool definitions)
~779 BTypical response size
Moderate attention impact (0.65% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "specpack": {
      "command": "npx",
      "args": [
        "specpack"
      ]
    }
  }
}

Runnable packages

npmspecpack0.1.0stdio

Remote endpoints

https://prompt-generator-website.com/mcpstreamable-http

What it can do

Tool inventory

Tools (5)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢list_project_types

The project types the spec generator knows (saas, ecommerce, business, marketplace, blog, webapp, landing), with what each covers.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢get_questionnaire(type)

The questions for one project type: universal questions first, then type-specific ones. Each has an id, a type (text, textarea, select, radio, multiselect, boolean, number), options where relevant, and sometimes a condition (ask it only when another answer matches). Answer from what you know of the project, then pass the answers to generate_spec. Only project_name and project_description are required; skipped questions fall back to defaults.

Input Schema

{
  "type": "object",
  "properties": {
    "type": {
      "type": "string",
      "enum": [
        "saas",
        "ecommerce",
        "business",
        "marketplace",
        "blog",
        "webapp",
        "landing"
      ],
      "description": "Project type id"
    }
  },
  "required": [
    "type"
  ],
  "additionalProperties": false
}
🟡generate_spec(type, answers, files)

Turns questionnaire answers into a complete build specification (stack, database schema, auth flows, pages, design system, SEO, security, legal, deployment, file structure) and the matching agent files. Deterministic: the same answers always give the same bytes. Values: select/radio = one option value, multiselect = array of option values, boolean = true/false, number = number. Returns the requested files; by default AGENTS.md (full spec + working agreement) and CLAUDE.md (imports AGENTS.md) — write them at the repository root. Uses one spec from the quota (2 free without an API key).

Input Schema

{
  "type": "object",
  "properties": {
    "type": {
      "type": "string",
      "enum": [
        "saas",
        "ecommerce",
        "business",
        "marketplace",
        "blog",
        "webapp",
        "landing"
      ]
    },
    "answers": {
      "type": "object",
      "description": "Question id => value, as described by get_questionnaire",
      "additionalProperties": true
    },
    "files": {
      "type": "array",
      "items": {
        "type": "string",
        "enum": [
          "spec.md",
          "AGENTS.md",
          "CLAUDE.md",
          ".cursor/rules/project.mdc",
          ".cursorrules",
          ".windsurfrules",
          ".github/copilot-instructions.md",
          "README.md"
        ]
      },
      "description": "Files to return. Default: [\"AGENTS.md\", \"CLAUDE.md\"]"
    }
  },
  "required": [
    "type",
    "answers"
  ],
  "additionalProperties": false
}
🟢draft_answers(description, type)

Asks the server's AI (Claude) to fill the whole questionnaire from a plain-language project description; returns the project type, the answers and the assumptions it made. Takes 10-40 s and consumes one AI draft (3 free without an API key). Prefer answering get_questionnaire yourself when you already know the project; use this when you only have a one-line idea. Review the assumptions with the user before calling generate_spec.

Input Schema

{
  "type": "object",
  "properties": {
    "description": {
      "type": "string",
      "description": "What the project is, for whom, and what it must do (10-4000 characters)"
    },
    "type": {
      "type": "string",
      "enum": [
        "saas",
        "ecommerce",
        "business",
        "marketplace",
        "blog",
        "webapp",
        "landing"
      ],
      "description": "Optional: force the project type"
    }
  },
  "required": [
    "description"
  ],
  "additionalProperties": false
}
🟢get_usage

Current plan and quota usage (specs and AI drafts) for the API key, or for this address when no key is set.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

Community

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Evidence

Recent observations

verifiedversion not recorded5 tools
verifiedversion not recorded5 tools