AirMCP
Website
Governed MCP runtime for the Apple ecosystem — verified control over Notes, Mail, Calendar, Shortcuts, and more.
Is AirMCP safe? Promising trust profile, but some evidence still deserves review.
Compare AirMCP
How does it stack up against its MCP Servers neighbours?
- Marketplaces MCP (RU) — Wildberries & Ozon +0.1 higher
- MCP Superset +0.1 higher
- Dynatrace MCP 0.1 lower
In detail: AirMCP scores 74.1/100 (Grade B), ranked #273 of 1378 tracked open-source AI agent projects, on evidence coverage B (3 of 5 independent signal types). The public evidence: its packages ship with cryptographic provenance; OSSF Scorecard rates its supply-chain practices 6.0/10; 66% of recent commits are signed; no published advisory affects its latest release (airmcp); last pushed 2026-10-12. Every point is earned from checkable signals — never paid placement. How scoring works →
How AirMCP could raise its score
Each line changes one public signal and recomputes with the live scoring function. The gains don't add up exactly, because the score is capped near the top.
- Raise the OSSF Scorecard from 6.0 to 9.0lowest checks: CII-Best-Practices 0, Code-Review 0, Fuzzing 0 +6.3 → 80.4 A · #75 of 781
- Sign every commit66% signed today +1.7 → 75.8 B · #133 of 781
Chain of custody
Scanners check what the code says. This traces who ships AirMCP and whether that has changed: from the source repository, through how changes are reviewed and released, to the package you install. These are the checks for OWASP ASI04 Agentic Supply Chain Vulnerabilities.
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Source Partly signed
github.com/heznpc/AirMCP, MIT, last pushed 2026-10-12. 66% of the last 100 commits carry a verified signature; the rest can't be tied to a verified identity.
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Review and release Mixed
OpenSSF Scorecard rates the repository's practices 6.0/10 (scanned Oct 15, 2026). The checks that decide who can get a change released:
- Code Review0
- Branch Protection3
- Signed Releases0
- Dangerous Workflow10
- Token Permissions0
- Pinned Dependencies9
All 18 Scorecard checks
Binary-Artifacts 10Branch-Protection 3CI-Tests 10CII-Best-Practices 0Code-Review 0Contributors 10Dangerous-Workflow 10Dependency-Update-Tool 10Fuzzing 0License 10Maintained 10Packaging 10Pinned-Dependencies 9SAST 10Security-Policy 10Signed-Releases 0Token-Permissions 0Vulnerabilities 2 -
Published packages Linked and attested
- npm airmcp Source link points back to this repo Build provenance attested
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What you install today No known advisories
Latest release checked: airmcp 2.16.5. No published advisory affects it (OSV, checked 2026-10-16).
Changes to this chain
- 2026-09-23 Package provenance attestation detected
Evidence behind this score
Coverage B: 3 of 5 independent evidence types found.
- GitHub repository data
- Package downloads
- Supply-chain checks
- Public actions (missing)
- Community mentions (missing)
Verify this score yourself
Every build re-issues AirMCP’s score as an Ed25519-signed credential, valid for 7 days. You can check it offline against HVTracker’s published key; if anyone changes a number after signing, verification fails.
What this score doesn’t check
It covers who ships the code, not what the code does. It doesn’t read tool descriptions or prompts for injected instructions, watch runtime behaviour, or find bugs nobody has disclosed yet. For that, run a content scanner before you connect it, such as Cisco MCP Scanner or Snyk Agent Scan.
How AirMCP compares in MCP Servers
- #156 Marketplaces MCP (RU) — Wildberries & Ozon 74.2 +0.1
- #157 MCP Superset 74.2 +0.1
- #158 AirMCP 74.1 this agent
- #159 Dynatrace MCP 74.0 −0.1
- #160 Discourse MCP 74.0 −0.1
Bars show each HVTrust score; the tick marks AirMCP’s 74.1.
Where the 74.1 comes from
HVTrust dimensions vs the MCP Servers average
74.1 / 100 · 100.0% confidenceAirMCP MCP Servers average (781 agents)
Quick Trust Read
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade B reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage B is separate — it grades how many independent signal types back the score (3 of 5), so a high score on thin evidence stays visible. Full methodology →
Rank Trend
Activity & Reach
Analysis
Activity Inputs
47.0 / 100Common questions about AirMCP
Does AirMCP publish package provenance?
Does AirMCP have an OpenSSF Scorecard?
Is AirMCP actively maintained?
What license does AirMCP use?
Are AirMCP's commits signed?
Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.
AI agent surface
MCP, providers, tool surface
These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →
- MCP signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Detected changes to AirMCP's runtime surface and supply-chain posture, from daily public-signal snapshots. A change here means our detectors see something different — a genuinely changed capability, or better evidence of an existing one.
Maintain AirMCP?
For maintainers
HVTrust scores AirMCP from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.
Reputation Timeline
Signal history
Embed Badge Badge guide for maintainers →
For maintainers
[](https://hvtracker.net/agents/airmcp)
<a href="https://hvtracker.net/agents/airmcp"><img src="https://hvtracker.net/badge/airmcp.svg" alt="HVTrust"></a>
Other agents in MCP Servers
GitHub REST API (repo, commits, stars, forks, license) · npm Registry (downloads, provenance) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON