mcp

Research-backed linting + generation for agent context files (CLAUDE.md, AGENTS.md, Cursor rules).

我該用這個嗎

品質與安全性

A
說明品質
100%
結構描述完整度
73%
命名品質
80%
汙染風險
100%
權限相符程度
100%
協定合規性
100%

根據工具定義與協定合規性的自動化分析。

上下文成本

~590Token(工具定義)
~1.5 KB典型回應大小
極小的注意力影響(128k 上下文的 0.46%)

這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。

安裝

一鍵安裝

將以下內容加入你的 `claude_desktop_config.json` 檔案:

{
  "mcpServers": {
    "mcp": {
      "url": "https://mcp.promptarch.ai/mcp"
    }
  }
}

遠端端點

https://mcp.promptarch.ai/mcpstreamable-http

它能做什麼

工具清單

工具(3)

🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢promptarch_lint_artifact(content, format, filename)

Lint an AI agent context file (CLAUDE.md, AGENTS.md, Cursor rules, Copilot instructions, memory files) with PromptArch's deterministic linter: ~30 research-backed rule families covering current-model anti-patterns (tool-forcing, reasoning-echo, sycophancy triggers, contradictions), per-tool size budgets, secrets/dangerous commands, and hidden-Unicode injection ("Rules File Backdoor"). Returns grade, 0-100 score, and line-anchored findings. Free: no account or credits needed.

輸入結構描述

{
  "type": "object",
  "properties": {
    "content": {
      "type": "string",
      "description": "The full file content to lint."
    },
    "format": {
      "description": "Override format auto-detection.",
      "type": "string",
      "enum": [
        "claude_md",
        "agents_md",
        "cursor_mdc",
        "copilot_instructions",
        "memory_file"
      ]
    },
    "filename": {
      "description": "Filename hint for format detection (e.g. CLAUDE.md).",
      "type": "string"
    }
  },
  "required": [
    "content"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢promptarch_list_artifact_types

List the artifact types promptarch_generate_artifact can produce from a project description.

輸入結構描述

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
⚪promptarch_generate_artifact(artifact, project_name, project_description, tech_stack, repo_structure, ...)

Generate an AI agent context artifact (e.g. context_pack, claude_md) from a project description. Requires a PromptArch API key configured as an Authorization: Bearer pk_... header on this MCP server. Consumes credits.

輸入結構描述

{
  "type": "object",
  "properties": {
    "artifact": {
      "type": "string",
      "enum": [
        "context_pack",
        "claude_md",
        "agents_md",
        "cursor_rule"
      ],
      "description": "Artifact id. See promptarch_list_artifact_types. Other Studio artifact types need artifact-specific inputs this tool does not accept."
    },
    "project_name": {
      "type": "string",
      "maxLength": 1900
    },
    "project_description": {
      "type": "string",
      "maxLength": 1900
    },
    "tech_stack": {
      "type": "string",
      "maxLength": 1900
    },
    "repo_structure": {
      "description": "Directory tree or structure summary. Max 1900 chars: summarize a large repo rather than pasting a full tree.",
      "type": "string",
      "maxLength": 1900
    },
    "commands": {
      "type": "string",
      "maxLength": 1900
    },
    "coding_conventions": {
      "description": "Conventions, invariants, house rules. Max 1900 chars.",
      "type": "string",
      "maxLength": 1900
    },
    "target_model": {
      "description": "Target model family (default Claude).",
      "type": "string",
      "maxLength": 100
    }
  },
  "required": [
    "artifact",
    "project_name",
    "project_description"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

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