proof-of-commitment
An MCP server for behavioral commitment and supply-chain risk analysis across packages, repositories, businesses, and domains.
Batch-audit up to 20 npm/PyPI dependencies for supply-chain risk with CRITICAL/HIGH/WARN flags.
Look up npm, PyPI, and Go module commitment profiles: age, download/version trends, publishers/owners, release cadence, GitHub activity, and score.
Assess public GitHub repositories via longevity, commit frequency, contributor depth, release cadence, and social proof.
Query domain engagement signals: unique verified visitors, repeat visit rate, and average time spent.
Search Norwegian businesses by name or org number for longevity, financial/operational health, and commitment score.
Use from MCP-compatible clients for dependency vetting, abandonware detection, vendor due diligence, and supply-chain audits.
Used as the technology stack for the landing page, but the MCP server itself provides behavioral scoring for npm/PyPI packages rather than direct Astro integration.
Provides behavioral commitment scoring and supply chain risk auditing for the Axios npm package, analyzing maintainer depth, download trends, and risk flags like CRITICAL status.
Used as the runtime environment for local development and deployment of the MCP server, but not a target service for the server's behavioral scoring capabilities.
Provides the hosting infrastructure (Cloudflare Workers) and edge caching for the MCP server backend and badge API endpoints.
Hosts the landing page for the Proof of Commitment web tool, while the MCP server itself runs on Cloudflare Workers.
Serves as the backend platform for the MCP server, handling API requests, badge generation, and behavioral data processing.
Provides behavioral commitment scoring and supply chain risk auditing for the Express npm package, analyzing maintainer count, download volume, and risk assessment.
Provides commitment scoring for GitHub repositories through the lookup_github_repo tool, analyzing longevity, commit frequency, and contributor depth.
Provides behavioral commitment scoring and supply chain risk auditing for the LangChain PyPI package as part of the proof-of-commitment tool's capabilities.
Provides behavioral commitment scoring and supply chain risk auditing for the Lodash npm package, analyzing maintainer count, download trends, and risk assessment.
Used for formatting audit results in PR comments and documentation, but not a target service for behavioral scoring.
Mentioned in the broader vision section as a card network identifying behavioral trust gaps, but not directly integrated with the MCP server's tools.
The primary ecosystem targeted for behavioral scoring of npm packages, with specific examples like chalk, zod, and axios analyzed for supply chain risk.
Provides behavioral scoring and risk auditing for npm packages through multiple tools including audit_dependencies and lookup_npm_package, analyzing download trends, maintainer depth, and release consistency.
Provides behavioral scoring and risk auditing for PyPI packages through tools including audit_dependencies and lookup_pypi_package, analyzing Python package ecosystems for supply chain risks.
Used as the local database (D1) for development and data storage in the Cloudflare Workers backend, but not a target service for behavioral scoring.
Mentioned as an example query target ('Is vercel/ai actively maintained?') for GitHub repository behavioral scoring through the MCP tools.
Mentioned in the broader vision section as a card network identifying behavioral trust gaps (Visa TAP), but not directly integrated with the MCP server's tools.
Used for GitHub Actions workflow configuration, but not a target service for the MCP server's behavioral scoring capabilities.
Provides behavioral commitment scoring and supply chain risk auditing for the Zod npm package, analyzing maintainer depth, download volume, and CRITICAL risk flags.
This server has a remotely hosted endpoint. Open its connector listing for connection details, authentication requirements, and setup instructions:
Proof of Commitment
Status: maintained — built and operated by Pico, an AI agent, at Commit. Bugs: GitHub issues.
Stars lie. Behavioral signals don't.
An MCP server and web tool that scores npm packages, PyPI packages, Rust crates, Go modules, and GitHub repos on behavioral commitment — signals that are harder to fake than stars, READMEs, or download counts.
$ npx proof-of-commitment axios zod chalk lodash minimatch
Scoring 5 npm packages... done in 3.0s
Package Risk Score Publishers Downloads Age Provenance
chalk 🔴 CRITICAL 72 1 432.9M/wk 14.6y —
minimatch 🔴 CRITICAL 78 1 634.1M/wk 14.9y —
lodash 🔴 CRITICAL 80 1 158.9M/wk 14.1y —
zod 🔴 CRITICAL 83 1 161.2M/wk 6.3y 🔐 verified
axios 🔴 CRITICAL 88 1 115.7M/wk 11.8y 🔐 verified
⚠ COMPROMISED — axios token theft (2026-03-30)
⚠ 5 CRITICAL packages found.
CRITICAL = sole active npm publisher + >10M weekly downloads (publish-access concentration risk)npm audit flags none of these. They're not vulnerabilities — they're attack-surface concentration. One stolen npm token, one phished maintainer, and a single push reaches the whole ecosystem (axios, March 30 2026 — happened).
The supply chain problem
26 of the 91 npm packages with >10M weekly downloads have a single npm publisher. Together they account for over 3 billion downloads per week. npm audit doesn't surface this. Stars don't either.
Four packages in a typical Node.js project are CRITICAL right now:
chalk — 432M downloads/week, 1 npm publisher
zod — 185M downloads/week, 1 npm publisher (30+ GitHub contributors)
lodash — 156M downloads/week, 1 npm publisher
axios — 113M downloads/week, 1 npm publisher (attacked March 30, 2026)
They won't appear in your package.json either — but these are in almost every project:
minimatch — 625M downloads/week, 1 npm publisher
glob — 366M downloads/week, 1 npm publisher
cross-spawn — 215M downloads/week, 1 npm publisher
Behavioral signals surface this. Stars and READMEs don't.
Related MCP server: pkgtruth
Quick install (MCP)
No login required. Add to any MCP-compatible AI tool and start querying supply chain risk.
Claude Desktop
Open ~/Library/Application Support/Claude/claude_desktop_config.json on macOS (config file reference) or %APPDATA%\Claude\claude_desktop_config.json on Windows, then add:
{
"mcpServers": {
"commit": {
"type": "streamable-http",
"url": "https://poc-backend.amdal-dev.workers.dev/mcp"
}
}
}Restart Claude Desktop. A tool icon appears in the chat input — ask it to audit your package.json.
Cursor
Open ~/.cursor/mcp.json (Cursor MCP docs) and add:
{
"mcpServers": {
"commit": {
"type": "streamable-http",
"url": "https://poc-backend.amdal-dev.workers.dev/mcp"
}
}
}Smithery (once indexed)
npx -y @smithery/cli install proof-of-commitment --client claudeTry it now
Terminal (zero install):
# New in v1.8.0: zero-arg auto-detect — cd into any project, run once:
npx proof-of-commitment
# Picks the highest-coverage manifest in cwd (package-lock.json > yarn.lock >
# pnpm-lock.yaml > pnpm-workspace.yaml > package.json; requirements.txt;
# Cargo.toml; go.sum > go.mod). When multiple ecosystems are present, the
# file with the most recent mtime wins.
# Explicit package list still works:
npx proof-of-commitment axios zod chalk
# Or point at a specific file:
npx proof-of-commitment --file package.json
npx proof-of-commitment --file package-lock.json # npm (transitive)
npx proof-of-commitment --file yarn.lock # yarn
npx proof-of-commitment --file pnpm-lock.yaml # pnpm
npx proof-of-commitment --file pnpm-workspace.yaml # pnpm monorepo
npx proof-of-commitment --pypi litellm langchain requests
npx proof-of-commitment --cargo serde tokio reqwest
npx proof-of-commitment --golang github.com/gin-gonic/gin golang.org/x/net
npx proof-of-commitment --file go.mod
npx proof-of-commitment --file go.sum # full transitive Go set
# JSON output for downstream tools:
npx proof-of-commitment --file package-lock.json --json | jq '.criticalCount'CI integration (v1.8.0+)
--fail-on=<level> turns the CLI into a one-line CI gate. No GitHub Action required.
# .github/workflows/supply-chain.yml
name: Supply Chain
on: [pull_request]
jobs:
audit:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with: { node-version: '20' }
- run: npx -y proof-of-commitment --fail-on=criticalLevels:
| Exit 1 when… |
| any package is flagged CRITICAL (publish-access concentration) |
| any package is CRITICAL or HIGH (score < 40) |
| never — report only |
Defaults: critical in CI (when CI=true is set, which every major CI runner does) and for --json output. Interactive (TTY, non-CI) keeps the v1.7 default of exit 0 — running locally won't break your shell habits.
The dedicated piiiico/commit-action@v1 is still the right choice when you want PR comments and step summaries; --fail-on is for minimal pipelines that just need a yes/no answer.
SARIF output for GitHub Code Scanning (v1.26.0+)
--sarif outputs SARIF 2.1.0 — the standard format for static analysis results. Upload it to GitHub Code Scanning and Commit findings appear in the Security tab alongside CodeQL and Snyk.
# .github/workflows/supply-chain.yml
name: Supply Chain
on: [pull_request]
jobs:
audit:
runs-on: ubuntu-latest
permissions:
security-events: write
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with: { node-version: '20' }
- run: npx -y proof-of-commitment --file package-lock.json --sarif --fail-on=none > results.sarif
- uses: github/codeql-action/upload-sarif@v3
if: always()
with:
sarif_file: results.sarif
category: commit-supply-chainCRITICAL and HIGH packages show as alerts in the repo's Security tab. Compromised packages (in the Commit incident registry) get a separate alert. --fail-on still controls the exit code independently — use --fail-on=critical to also block the PR.
Web demo (no install): getcommit.dev/audit — paste your packages, see risk scores in seconds.
IDE Hooks (Cursor + Claude Code + Windsurf)
poc hook installs a supply chain gate for Cursor (beforeShellExecution), Claude Code (PreToolUse), and Windsurf (pre_run_command) in one command. The same hook script intercepts package installs from any agent, auto-detects which client called it, and blocks CRITICAL packages before they run.
# Install for the current project (writes .cursor/hooks.json + .claude/settings.json + .windsurf/hooks.json):
poc hook
# Or protect every project for your user:
poc hook --global
# Narrow to one client:
poc hook --cursor # only .cursor/hooks.json
poc hook --claude-code # only .claude/settings.json
poc hook --windsurf # only .windsurf/hooks.json
# Remove (cleans all three):
poc hook --uninstallThe hook writes .cursor/hooks.json, .claude/settings.json, and .windsurf/hooks.json (project) or the equivalents under ~/ (with --global). When Cursor, Claude Code, or Windsurf runs npm install axios, pip install litellm, cargo add serde, or go get github.com/gin-gonic/gin, the hook calls the Commit API and either blocks, warns, or allows — in under 500ms.
What gets intercepted:
Package manager | Example command |
npm / npx |
|
pnpm |
|
yarn |
|
pip / pip3 / uv |
|
cargo |
|
go |
|
Why this matters: Supply chain attacks now happen in minutes. The Shai-Hulud worm (May 2026) compromised 637 packages in 39 minutes and specifically targeted AI coding assistants — planting persistence hooks in .claude/settings.json and .vscode/tasks.json. When your AI assistant installs a dependency, it bypasses the human review that used to be the last line of defense. poc hook puts a gate back in — same gate, whether Cursor, Claude Code, or Windsurf is driving.
Default behavior: CRITICAL packages (sole active npm publisher + >10M downloads/week — the exact LiteLLM/axios attack profile) are blocked. HIGH packages trigger an "ask user" prompt (Cursor/Claude Code) or are blocked with a message (Windsurf). Set COMMIT_HOOK_SEVERITY_BLOCK=HIGH to block both.
With an API key: poc login sk_commit_… before running poc hook — the key is embedded in the hook config and lifts the rate limit.
Get notified before the next attack
The CLI tells you what's risky today. A free API key unlocks monitoring — score recomputation across the packages you depend on, with alerts when one degrades (publisher drops, release stalls, score falls ≥10 points).
Open (free): Watch 3 packages · weekly digest every Monday
Developer ($15/mo): Watch 15 packages · daily scans · instant email alerts
Get a free API key → (no card, 30 seconds · 200 audits/day included)
npm install -g proof-of-commitment # then:
poc watch axios --email you@company.com # free key + monitoring in one step
poc watch chalk # add more packages (3 free)
poc init # add CI gate to this repoGitHub Action
Add supply chain auditing to any CI pipeline in 30 seconds — auto-detects packages from package.json or requirements.txt, posts results as a PR comment, writes to GitHub Step Summary, and optionally fails on CRITICAL packages.
Use the dedicated action at piiiico/commit-action:
# .github/workflows/supply-chain.yml
name: Supply Chain Audit
on:
pull_request:
paths: ['package.json', 'package-lock.json', 'bun.lock']
jobs:
audit:
runs-on: ubuntu-latest
permissions:
pull-requests: write
steps:
- uses: actions/checkout@v4
- uses: piiiico/commit-action@v1
with:
fail-on-critical: true # blocks merges on CRITICAL packages
comment-on-pr: true # posts results as a PR commentWhen comment-on-pr: true (default), the action automatically posts the audit table as a comment on the pull request — and updates the same comment on re-run, so you don't get comment spam. Reviewers see the risk table without leaving the PR.
Inputs:
Input | Default | Description |
| (auto) | Comma-separated package names (auto-detected from |
| (auto) | Path to |
|
| Fail the workflow if CRITICAL packages are found |
|
| Max packages to audit when auto-detecting |
|
| Include |
|
| Post audit results as a PR comment (requires |
| (none) | Commit Pro API key — enables batch requests and 10K requests/month |
| (prod) | Override API endpoint (useful for self-hosting) |
Outputs: has-critical, critical-count, audit-summary (markdown table, also written to Step Summary).
Free vs Pro: Without an API key, packages are audited one at a time (with delays to respect rate limits). With a Pro API key, all packages are audited in a single batch request — faster and with higher monthly limits.
Example PR comment / Step Summary output:
| Package | Risk | Score | Publishers | Downloads/wk | Age |
|---------|-------------|-------|------------|--------------|-------|
| chalk | 🔴 CRITICAL | 75 | 1 | 380M | 12.7y |
| zod | 🔴 CRITICAL | 83 | 1 | 133M | 6.1y |
| axios | 🔴 CRITICAL | 89 | 1 | 93M | 11.6y |README Badges
Add a Commit Trust badge to any npm package you maintain or depend on:
Examples:
Package | Badge URL |
chalk |
|
react |
|
express |
|
@babel/core |
|
Grades: 🟢 OK (75+) · 🟠 WARNING (40–74) · 🔴 CRITICAL (<40 or sole active npm publisher with 10M+ weekly downloads)
Badges are cached 1 hour. No API key needed.
Also supports PyPI, Cargo, Go modules, and the full ecosystem-specific format:



REST API
No API key. No install.
curl https://poc-backend.amdal-dev.workers.dev/api/audit \
-X POST \
-H "Content-Type: application/json" \
-d '{"packages": ["axios", "zod", "chalk", "lodash", "express"]}'{
"count": 5,
"results": [
{
"name": "chalk",
"ecosystem": "npm",
"score": 75,
"maintainers": 1,
"weeklyDownloads": 398397580,
"ageYears": 12.7,
"trend": "stable",
"riskFlags": ["CRITICAL"],
"scorecardScore": 3.6, // null if no GitHub repo
"hasDangerousWorkflow": false // null if no Scorecard data
},
...
]
}12 MCP tools
Tool | Description |
| Batch risk audit for up to 20 npm/PyPI/Cargo/Go packages |
| Fetch a repo's package.json/requirements.txt and audit every dep |
| Map an npm package's full dependency tree (incl. transitive CRITICAL deps) |
| Single npm package behavioral profile |
| Single PyPI package behavioral profile |
| Single Rust crate behavioral profile (crates.io) |
| Single Go module behavioral profile (proxy.golang.org + GitHub) |
| GitHub repo commitment score (longevity, commit frequency, contributor depth) |
| Norwegian business register — operating years, employees, financials |
| Same, by org number |
| Browser extension behavioral data (unique verified visitors, repeat rate) |
| Create a free API key in-chat — no browser needed, key returned instantly |
Anonymous: 15 requests/IP/UTC day across both /mcp and /api/audit. Free key (no card, 30s signup at https://getcommit.dev/get-started): 200/day. Higher tiers at https://getcommit.dev/pricing.
What the score measures
Each package is scored 0–100 across:
Longevity — How long has the package existed? Abandoned packages get reactivated for attacks.
Publisher depth — Single npm publisher + millions of weekly downloads = the attack surface LiteLLM exploited. (Publisher = person with npm publish access, distinct from GitHub contributors.)
Release consistency — Regular releases signal active oversight. Long gaps = vulnerability accumulation.
Download trend — Growing packages attract more scrutiny (and attacks). Stable = lower profile.
OpenSSF Scorecard — Process security (code review enforcement, branch protection, CI/CD safety). Separate from behavioral signals. High Scorecard ≠ safe from credential theft attacks.
Both axios (8.1/10 Scorecard) and chalk (3.6/10 Scorecard) score CRITICAL on behavioral signals. They measure different attack surfaces — Scorecard catches process gaps, behavioral signals catch publisher concentration.
Risk flags:
CRITICAL— single npm publisher + >10M weekly downloads (exact LiteLLM/axios attack profile)HIGH— package <1yr old + rapid adoptionWARN— no release in 12+ months
Real data points
# packages you know about:
chalk — score 75, 1 publisher, 432M/week ⚑ CRITICAL
zod — score 83, 1 publisher, 185M/week ⚑ CRITICAL (30+ GitHub contributors)
lodash — score 81, 1 publisher, 156M/week ⚑ CRITICAL
axios — score 88, 1 publisher, 113M/week ⚑ CRITICAL (attacked Mar 30 2026)
express — score 90, 5 publishers, 95M/week
# packages probably not in your package.json, definitely in your lock file:
minimatch — score 78, 1 publisher, 625M/week ⚑ CRITICAL
glob — score 80, 1 publisher, 366M/week ⚑ CRITICAL
cross-spawn — score 72, 1 publisher, 215M/week ⚑ CRITICAL
# post-attack:
litellm — score 74, 1 publisher ⚑ CRITICAL (supply chain attack Mar 2026)
# Rust crates (new in v1.3.0):
serde — score 78, 1 owner, 13M/week ⚑ CRITICAL (dtolnay sole owner)
tokio — score 89, 2 owners, 10M/week
reqwest — score 85, 1 owner, 8M/week ⚑ HIGHWhy behavioral signals
The LiteLLM attack (March 2026) and axios attack (March 30, 2026) followed the same pattern: stolen credentials → malicious package pushed → 97M+ machines exposed. Both packages flag CRITICAL by these metrics today, on the single-account condition the attackers used. The scores were computed after the attacks: a retrodiction, not a prediction.
Declarative signals (stars, README quality, CI badges) don't capture this risk. Behavioral commitment does.
Blog
The LinkedIn Backdoor: Why npm audit Missed a 250-Line Attack — A fake recruiter clone attack hid malware in test files and ran it via npm lifecycle scripts. npm audit: silent. What behavioral signals would have flagged.
axios: The Structural Case — axios flags CRITICAL (sole npm publisher) on the condition its March 30, 2026 token theft used. Scored after the attack, not before.
Stack
Layer | Technology |
Backend | Cloudflare Workers + D1 |
MCP | Model Context Protocol SDK |
Data | npm registry, PyPI, crates.io, proxy.golang.org, deps.dev, GitHub API, Brønnøysund (NO) |
Landing | Astro + Cloudflare Pages |
Roadmap
Planned, not promised. The project is early-stage — contributions welcome on any of these.
Feature | Status | Notes |
Cargo (Rust) registry support | ✅ Live | MCP tool, REST API, badge endpoint — |
Go modules support | ✅ Live | proxy.golang.org + deps.dev + GitHub-primary scoring — |
Score breakdown visualization | Planned | Chart component for the 5 dimensions on getcommit.dev/audit |
| ✅ Live |
|
pnpm workspace monorepo support | ✅ Live |
|
Historical score tracking | Planned | Trend charts — was this package getting riskier over time? |
Org-level dashboards | Planned | Aggregate risk view across all repos in a GitHub org |
See open issues for things you can help with today.
The broader vision
Supply chain auditing is the first tool. The underlying primitive is a commitment graph — behavioral signals that replace content-based trust across any domain.
When content is free to fake (reviews, stars, READMEs), commitment becomes the signal. A publisher who has shipped 847 releases over 12 years is a different kind of commitment than one who published once in 2023.
The same logic applies to websites, businesses, and AI agents. Two card networks have independently named this gap: Mastercard Verifiable Intent §9.2 explicitly lists behavioral trust as "not covered." Visa TAP identifies agents without answering whether to trust them.
Proof of Commitment is the trust layer they're pointing at.
Run locally
bun install
bun run dev:backend # local server with SQLite
bun run test:e2e # E2E test with mock World IDDeploy:
bun run deploy # deploys to Cloudflare WorkersReleasing
Publish is triggered automatically when a tag v* is pushed, or manually via GitHub Actions workflow_dispatch.
Funnel smoke gate
Before npm publish runs, the CI workflow executes scripts/funnel-smoke.sh — a local-mock pre-publish check that exercises four key funnel paths:
Path | What it tests | Bug class caught |
A | CLI audit with | v1.20.0: missing |
B | CLI audit anonymous, 429 → message + | 429 handling / CTA surfacing |
C | cursor-hook (Cursor stdin) 429 → | v1.21.0: silent |
D | cursor-hook (Claude Code | v1.22.0: wrong-shape reply when Claude Code drives → silent allow / mis-attributed conversion |
Any path failure blocks the release. The gate runs a local Python mock server so it's deterministic in CI and doesn't depend on production rate-limit state.
Optional CI secret: Set COMMIT_TEST_API_KEY in GitHub repo secrets to use a real API key for Path A. Falls back to a mock key that the local server accepts unconditionally.
Run locally:
bash scripts/funnel-smoke.shAvailable Tools
8 toolsaudit_dependenciesAInspect
Batch-score multiple npm or PyPI packages for supply chain risk. Takes a list of package names and returns a risk table sorted by commitment score (lowest = highest risk first).
Risk flags:
CRITICAL: single npm publisher + >10M weekly downloads (publish-access concentration risk)
HIGH: new package (<1yr) + high downloads (unproven, rapid adoption = supply chain risk)
WARN: no release in 12+ months (potential abandonware)
WARN: dormant publishers with current scope access — contributors who stopped publishing but retain npm tokens (the Mastra incident vector, June 2026)
Perfect for auditing a full package.json or requirements.txt — paste your dependency list and get a prioritized risk report.
Examples: score all deps in a project, compare two similar packages, identify abandonware before it becomes a CVE.
Inputs: packages (required), ecosystem.
lookup_businessBInspect
Search for a Norwegian business and get its commitment profile from public data (Brønnøysund Register Centre). Returns real commitment signals that can't be faked:
Temporal commitment: how long the business has operated
Financial commitment: revenue, profitability, equity health
Operational commitment: employee count, active status
Overall commitment score (0-100)
Data source: Norwegian government registers (Brreg). No user-contributed data needed — immediate trust verification for any Norwegian business.
Inputs: query (required), maxResults.
lookup_business_by_orgAInspect
Look up a specific Norwegian business by organization number and get its commitment profile from public data (Brønnøysund Register Centre). Returns real commitment signals: longevity, financial health, operational activity, and overall commitment score.
Inputs: orgNumber (required).
lookup_github_repoAInspect
Get a behavioral commitment profile for any public GitHub repository. Returns real signals: how long the project has existed, recent commit frequency, contributor community size, release cadence, and social proof. These are behavioral commitments — harder to fake than README claims.
Useful for: vetting open-source dependencies, evaluating AI tools/frameworks, assessing vendor reliability. Examples: "vercel/next.js", "facebook/react", "https://github.com/piiiico/proof-of-commitment"
Inputs: repo (required).
lookup_go_moduleAInspect
Get a behavioral commitment profile for any Go module on proxy.golang.org. Takes a full module path (e.g., "github.com/gin-gonic/gin", "golang.org/x/net", "k8s.io/client-go", "gopkg.in/yaml.v3") and returns real signals: module age, version count, publish cadence, GitHub contributors (the closest equivalent to "publishers" since Go has no centralized publisher concept — git push access is the publish equivalent), GitHub stars, OpenSSF Scorecard score.
The Go ecosystem has no centralized download counter, so this profile is GitHub-primary — the linked source repository's activity, contributor count, and Scorecard carry more weight than for npm/PyPI/Cargo. Stars are used as the popularity proxy.
Useful for: vetting Go dependencies before adding to go.mod, identifying abandonware, supply chain risk assessment. Examples: "github.com/gin-gonic/gin", "golang.org/x/crypto", "github.com/spf13/cobra", "k8s.io/api"
Inputs: module (required).
lookup_npm_packageAInspect
Get a behavioral commitment profile for any npm package. Returns real signals: package age, download volume and trend (growing/stable/declining), release consistency, npm publisher count, GitHub contributor count, and linked GitHub activity.
Also returns publisherLifecycle — cross-referencing current maintainers against per-version publish history to flag dormant publishers who still hold npm scope access. The Mastra incident (June 2026) exploited exactly this: a contributor dormant since 2024 with never-revoked scope access.
Supply chain attacks target packages with low publisher depth (few people with npm publish access). Behavioral signals reveal what download counts hide.
Useful for: vetting dependencies, identifying abandonware, due diligence on open-source packages. Examples: "langchain", "@anthropic-ai/sdk", "express", "litellm"
Inputs: package (required).
lookup_pypi_packageAInspect
Get a behavioral commitment profile for any PyPI (Python) package. Returns real signals: package age, download volume and trend, release consistency, publisher/owner count, and linked GitHub activity.
Supply chain attacks target Python packages — LiteLLM (97M downloads/mo) was compromised via stolen PyPI token in March 2026. Behavioral signals reveal what star counts hide.
Useful for: vetting Python dependencies, identifying abandonware, supply chain risk due diligence. Examples: "langchain", "litellm", "openai", "anthropic", "requests", "fastapi", "pydantic"
Inputs: package (required).
query_commitmentAInspect
Query verified behavioral commitment data for a domain. Returns aggregated signals: unique verified visitors, repeat visit rate, and average time spent. These prove real human engagement — harder to fake than reviews or content.
Inputs: domain (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 8 tools
The package-ecosystem lookups (npm, PyPI, Go, GitHub) are clearly scoped to distinct registries, and audit_dependencies is obviously batch-oriented. The only real overlap is lookup_business vs lookup_business_by_org, which differ mainly by input (name search vs org number), and query_commitment's domain-based scope is somewhat fuzzy against the package lookups since package profiles also aggregate engagement signals.
All eight tools use snake_case verb_noun form, with six sharing a lookup_ prefix and the rest using query_/audit_ verbs appropriately. Minor inconsistency in the noun portion of the lookup family (github_repo vs go_module vs pypi_package vs npm_package vs business), but the pattern remains predictable.
Eight tools is well inside the sweet spot for a registry/commitment-scoring server. Each tool maps to a distinct data source or aggregation mode, and none feels redundant padding.
The surface covers Norwegian business data, four code-ecosystem sources, domain engagement, and batch risk auditing — a coherent lifecycle from single lookup to prioritized audit. Gaps remain: audit_dependencies only handles npm/PyPI (not Go/GitHub), and other major ecosystems (Cargo, RubyGems, Maven) have no lookup at all, but agents can work around these.
Maintenance
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Safety grade (A to F) for any public GitHub repo, in plain English, before you install it.
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