ideaudit MCP server
The scoring behind an audit allowed to say no. Twenty deterministic tools, offline, no account.
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If you have run it, two minutes of your experience saves the next person an afternoon.
ideaudit tools (21, 1 write)
write = sends, deletes, buys or postscompute_barrierFreeCompute barrier_score (0-24) + label (PRISTINE/OPEN/COMPETITIVE/CROWDED) from competitor counts + SERP noise fraction.
compute_budget_proofFreeCompute budget_proof_score (0-10) + label (STRONG/CONFIRMED/WEAK/ABSENT) + purchase_intent_pct from pricing hits + review-site hits + intent mentions.
compute_build_complexityFreeCompute 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_scoresFreeCompute 12 deterministic collection scores (0-100) + badges + death reason for an enriched idea. Pure math. No external calls.
compute_crossed_matrixFreeCrossed-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 persists; meant for the dashboard "view as [archetype]" dropdown and for previewing a verdict before committing to it.
compute_dealbreakers_v2FreeMethodology 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) PLUS crossed verdict (observer-perturbed weights, risk-tolerance shifted thresholds) PLUS 5-row archetype matrix. The KILL gate (≥2 blockers / score<50) is observer-invariant — fatal stays fatal.
compute_funding_momentumFreeCompute funding_momentum_score (0-10) + badge (HOT/WARM/COOL/COLD) from tier-weighted funding-article hit counts.
compute_hiring_demandFreeCompute hiring_demand_score (0-10) from priority-weighted ATS site hit counts (use registries/hiring-sources for priorities).
compute_lrs_compositeFreeCompose 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_lrs_composite_v2FreeLRS 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 outcome calibration exists). buildComplexityPenalty 0-10 subtracted from score. sectorProfile (ai_native/creator/crypto) opt-in reshuffles SV→0.16, X→0.20. Labels: THE_ROAR (≥80) / PROMISING (≥60) / EXPERIMENTAL (≥40) / WEAK_SIGNAL (<40).
compute_monetizationFreeCompute monetization_score (0-21) + label + has_pricing_anchors from pricing anchors + model tags + deal cycle hint.
compute_multi_source_tamFreeMulti-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 deviation when n≥4. Returns the extracted dollar amounts + consensus median + an agreement score 0..1, where 1 means every source lands within 20% of the median.
compute_ppc_spend_signalFreeWave 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_velocityFreeCompute search_velocity_score (0-25) from Trends timeline values + rising queries count + geo region count.
compute_search_velocity_v2FreeSearch 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 normalized 0-100 within window). trendNorm is derived internally from trendsTimelineValues. Trends peak<50 zeroes the trend component (Yotpo SEO floor). Optional daysSinceLastSignal applies exponential freshness decay (search half-life 90d).
compute_social_painFreeCompute social_pain_score (0-30) + total mentions + dominant perspective (business/consumer/trend/mixed).
compute_urgency_compositeFreeCompose composite_urgency_score (0-10) + badge (LOW/MEDIUM/HIGH/VERY_HIGH/EXTREME) from 3 sub-scores: news, pain, hiring.
compute_x_signalFreeCompute x_signal_score (0-20) + recency share + positivity rate from X/Twitter mention counts.
derive_kill_criteriawrite actionFreeDerive 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 / cleared. Replaces prose kill criteria, which are tautologies that can never fire.
get_startedFreeWhat 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.
validate_unit_economicsFreeSanity-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, detail}], derived{ratios}}. Skills MUST regenerate the row when ok=false (block-severity errors); warn-severity errors should be surfaced in the final report but do not gate publication. No LLM calls.
Public scan report
scanner v0.1.9 · 2026-09-20 · same rubric, same numbers if you re-run it
- Code scan13 source files scanned25/25
- Live reliabilityremote reachable in 1050ms20/20
- Tool poisoning21 tool descriptions checked15/15
- Auth qualityAPI key sent as a header8/15
- Maintenancelast push 12 days ago15/15
- Maintainer identitynamespace and repository owner differ; GitHub account older than a year; website matches verified namespace8/10
What the publisher says
From the ideaudit repository's README, as published. We do not edit it. Read it on GitHub
ideaudit-tools
The deterministic scoring behind ideaudit, as a local MCP server. No account, no key, no network, no model calls — just the arithmetic.
claude mcp add ideaudit-tools -- npx -y @inite/ideaudit-toolsListed in the MCP registry as studio.inite/ideaudit-tools, which carries both ways in: this package over stdio, and the hosted server over HTTP. Installing straight from this repository — npx -y github:inite-ai/ideaudit-mcp — also works and runs the same code.
Why this is published
The product's claim is that it is an audit allowed to say no. A verdict nobody can inspect is a verdict nobody has to believe, so the part that produces the number is open — including the number that says no. You can read how three lens scores become KILL, disagree with the thresholds, and argue about the arithmetic rather than about our word.
It is also the honest shape of the system. The server makes zero model calls; judgement lives in the skills, determinism lives in the tools. These are the tools.
What runs locally
Twenty tools, every one a pure function of its input:
computedealbreakersv2 is the one that decides. Stage-aware weights, confidence-weighted lens scores, and a deliberately risk-asymmetric verdict: GO needs a score ≥ 80 and zero red flags and average confidence ≥ 0.6, while the KILL gate is observer-invariant — a founder profile shifts every threshold above the gate, and none of them below it. You cannot buy a better answer by describing yourself more favourably. There is a test that says so.
Same input, same output as the hosted server — because it is the same specification object, imported rather than reimplemented. A test asserts that identity rather than comparing two copies, so the two cannot drift.
Where to look
Be told where the numbers are rather than hunt for them:
what it returns. compute-dealbreakers-v2.ts is the verdict.
- src/specs/.ts** — one file per tool: what it accepts, what it means,
observer-invariant KILL gate is checked against all five archetypes.
- src/server.ts — the whole server, including what it refuses.
- src/tests/parity.test.ts — the claims above, as assertions. The
dozen lines and every constant is visible: 0.6 off the score per direct competitor, 0.2 per adjacent, six points of range spent on SERP noise, and labels at 18 / 12 / 6. Disagree with those numbers, not with our word.
- dist/bundle.js — the arithmetic, un-minified. computeBarrier is a
That last one is a build artefact and reads like one — the commented source of the maths lives in the monorepo this repository is mirrored from, and is not here. If you want the reasoning behind a threshold rather than the threshold itself, open an issue and ask; that is a cheaper conversation than either of us pretending.
What needs the hosted server
Not withheld to make a point — these genuinely need somewhere to keep things and someone to pay for them:
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Install directly
claude mcp add --transport http ideaudit-tools https://api.inite.studio/mcp
ideaudit: common questions
- Is ideaudit MCP server safe?
- Yes, by our scan: it is graded A (91/100). Read the ideaudit safety report
- How do I install ideaudit?
- It runs remotely at api.inite.studio. Add it to Claude Code, Claude Desktop or Cursor with the snippets above, or call it through the mcp.market gateway without installing anything.
- Does ideaudit need an API key?
- Yes. The registry entry asks for
Authorization. - Is ideaudit maintained?
- The last commit was 14 days ago (2026-09-07). The latest release is v1.1.0.
- Is ideaudit up?
- 100% of our last 7 checks got an answer. We check remote servers about four times a day.