ideaudit

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

• 连接方式: 电脑或云端
• 传输方式: stdio, Streamable HTTP
• 分类: 其他
• 你需要填写：Authorization

安装

选择你使用的 AI 应用，然后复制设置。

你需要

• 在云端运行无需安装任何东西，通过互联网连接
• npm已安装 Node.js（用于 npx 命令）

你用的是哪个应用？

{
  "mcpServers": {
    "ideaudit-tools": {
      "command": "npx",
      "args": [
        "-y",
        "@inite/ideaudit-tools"
      ]
    }
  }
}

claude mcp add --transport http ideaudit-tools https://api.inite.studio/mcp --header 'Authorization: your-value'

claude mcp add ideaudit-tools -- npx -y @inite/ideaudit-tools

{
  "mcpServers": {
    "ideaudit-tools": {
      "url": "https://api.inite.studio/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

{
  "mcpServers": {
    "ideaudit-tools": {
      "command": "npx",
      "args": [
        "-y",
        "@inite/ideaudit-tools"
      ]
    }
  }
}

{
  "servers": {
    "ideaudit-tools": {
      "type": "http",
      "url": "https://api.inite.studio/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

{
  "servers": {
    "ideaudit-tools": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@inite/ideaudit-tools"
      ]
    }
  }
}

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

• Authorization 机密 HTTP header
  Bearer token from https://inite.studio/settings/keys. Optional: with no Authorization header the same endpoint answers on a guest lane — the twenty deterministic scoring tools, including the verdict,…

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档，检查于 2026年11月10日。

通过互联网连接，适用于

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

在你的电脑上运行，适用于

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

全部应用及其优缺点 →

它能做什么

工具名称和描述与服务器在 2026年11月9日 报告的完全一致。这些内容由作者撰写，不是我们写的；我们以纯文本形式显示。

• get_started

  What this server is, what it will do for you right now without an account, and what an account adds. Call this first if you have no API key — it answers in one round trip instead of sending you to a website.

• compute_barrier

  Compute barrier_score (0-24) + label (PRISTINE/OPEN/COMPETITIVE/CROWDED) from competitor counts + SERP noise fraction.

• compute_budget_proof

  Compute budget_proof_score (0-10) + label (STRONG/CONFIRMED/WEAK/ABSENT) + purchase_intent_pct from pricing hits + review-site hits + intent mentions.

• compute_build_complexity

  Compute build_complexity_penalty (0-10, higher = worse) + per-factor breakdown. Hard tags: ml/realtime/blockchain/hardware/compliance/custom-ai/regulated/on-device-ai/iot.

• compute_collection_scores

  Compute 12 deterministic collection scores (0-100) + badges + death reason for an enriched idea. Pure math. No external calls.

• compute_crossed_matrix

  Crossed-product audit explorer. Same input as compute_dealbreakers_v2 — returns substrate verdict (no-observer baseline) + crossed verdict (when observer supplied) + a 5-row matrix of {solo, cofounded_technical, cofounded_business, domain_expert, serial} archetype verdicts. Never

• compute_dealbreakers_v2

  Methodology v2 dealbreakers — stage-aware weights + confidence-weighted lens scoring + risk-asymmetric verdict (GO requires score≥80 AND zero red flags AND avg confidence≥0.6). Optional `observer` triggers the crossed-product pipeline: substrate verdict (no-observer baseline) PLU

• compute_funding_momentum

  Compute funding_momentum_score (0-10) + badge (HOT/WARM/COOL/COLD) from tier-weighted funding-article hit counts.

• compute_hiring_demand

  Compute hiring_demand_score (0-10) from priority-weighted ATS site hit counts (use registries/hiring-sources for priorities).

• compute_lrs_composite_v2

  LRS composite v2 — 6 components (SV, Pain, Barrier, Monet, X-Signal, Budget-Proof). Default Python weights 0.18/0.22/0.18/0.14/0.18/0.10 sum=1.0. Returns BOTH weighted score and equal-weight baseline (per OECD Handbook + Greco 2018 — equal-weight is defensible default when no out

• compute_lrs_composite

  Compose lrs_final_100 (0-100) + label (WEAK/EMERGING/GOOD/STRONG/ELITE) + leaderboard_eligible flag + sub-percent breakdown. Weights: sv 0.25, sp 0.30, barrier 0.25, monetization 0.20.

• compute_monetization

  Compute monetization_score (0-21) + label + has_pricing_anchors from pricing anchors + model tags + deal cycle hint.

• compute_multi_source_tam

  Multi-source TAM consensus. Pass 2-3 sources of market-size text. Optional `estimateYear` per source — when supplied, the result includes yearRange and a hasStaleData flag (true if the span exceeds 5 years). Outliers are dropped by modified Z-score over the median absolute deviat

• compute_ppc_spend_signal

  Wave 5 N.4 — compute ppc_spend_score (0-10) + label (STRONG/CONFIRMED/WEAK/ABSENT) + market_saturation from PPC traffic projection (avgCpcUsd, totalMonthlySpendUsd, optional competitorBidders + competition). Feed numbers from dataforseo_ad_traffic.

• compute_search_velocity_v2

  Search velocity (0-25) v2 — canonical 0.40*volume + 0.30*trend + 0.20*intent + 0.10*geo. CRITICAL: externalVolumeNorm MUST come from external sources (Amazon BSR / app store installs / job-board postings) — NOT the Trends timeline (would double-count, since Trends is itself norma

• compute_search_velocity

  Compute search_velocity_score (0-25) from Trends timeline values + rising queries count + geo region count.

• compute_social_pain

  Compute social_pain_score (0-30) + total mentions + dominant perspective (business/consumer/trend/mixed).

• compute_urgency_composite

  Compose composite_urgency_score (0-10) + badge (LOW/MEDIUM/HIGH/VERY_HIGH/EXTREME) from 3 sub-scores: news, pain, hiring.

• compute_x_signal

  Compute x_signal_score (0-20) + recency share + positivity rate from X/Twitter mention counts.

• derive_kill_criteria

  Derive a falsifiable, data-driven list of kill criteria from upstream signals — the outputs of validate_unit_economics and compute_dealbreakers_v2, plus an ICP drift count. Returns one row per rule with {rule, threshold, status, evidence?}, where status is tripped_now / monitor /

• validate_unit_economics

  Sanity-check a unit-economics row before publishing it in a business-model slide. Catches the math-drift class of failures (customers × ARPU ≠ revenue), enforces the LTV/CAC ≥ 1.5 floor, the cohort-positivity check, and CAC payback bounds. Returns {ok, errors[{rule, severity, det

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月10日

• ✓ 通过

  作者与仓库一致

  注册名称已通过域名 inite.studio 验证（注册中心会核实域名所有权）

• ✓ 通过

  仍在维护

  代码最后更新于11天前

• … 尚未检查

  有许可证

  我们还没有从 GitHub 读取这个仓库

• ✓ 通过

  端点有响应

  在 79 毫秒内响应（HTTP 200）

• – 不适用

  使用 OAuth 登录

  无需登录

• ✓ 通过

  工具描述中没有隐藏指令

  已读取 21 个工具描述，未发现针对 AI 的隐藏指令

与“其他”中的其他服务器比较i

• 星标数多于此分类中其他 19103 个服务器的 0%
• 发布到注册中心的时间比此分类中其他 19103 个服务器的 32% 更新
• 基础检查结果等于或优于此分类中其他 19103 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

作者的 README

claude mcp add ideaudit-tools -- npx -y @inite/ideaudit-tools

$ compute_dealbreakers_v2 {"auditId": "…", …}

claude mcp add ideaudit --transport http https://api.inite.studio/mcp \