How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade D reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Full methodology →
Signals refreshed2026-06-22 00:01 UTC·Repo last pushed 4 days ago
Rank Trend
2026-06-202026-06-21
Activity & Reach
Stars
15.2k
Forks
1.2k
Last Push
2026-06-18
4 days ago
Commits (4 wk)
23
Downloads (7d)
—
HN mentions (30d)
—
Open Issues
16
Rank Change
▼1
was #257
Analysis
HVTrust Dimensions
25.3 / 100 · 50.0% confidence
Safety / IntegrityOSSF, provenance, signatures
4.1 / 25
Identity / ProvenanceListing and build link
10.8 / 18
TransparencyLicense and public checks
8.5 / 17
MaintenanceFreshness and commits
17.2 / 20
AdoptionStars and downloads
10.0 / 20
Activity Inputs
81.3 / 100
StarsRepository reach
25.1 / 30
FreshnessLast push recency
24.4 / 25
ActivityRecent commits
17.2 / 25
CommunityFork signal
14.3 / 20
Supply Chain Trust
Package Provenance
None
No package attestations found
OSSF Scorecard
—
Not available
Signed Commits
82%
of last 100 commits verified
Is Figma Context MCP safe?
Public trust evidence for Figma Context MCP is thin: several supply-chain signals are missing or weak. This does not mean the project is unsafe — it means an outside observer cannot easily verify the usual integrity checks. Treat with extra scrutiny.
Does Figma Context MCP publish package provenance?
No published build provenance is currently detected for Figma Context MCP. This is common for open-source projects but means consumers cannot independently verify that the package on the registry matches the GitHub source.
Does Figma Context MCP have an OpenSSF Scorecard?
No OpenSSF Scorecard data is currently published for Figma Context MCP. Maintainers can enable the Scorecard GitHub Action to get a public score; without it, automated supply-chain hygiene is harder for outsiders to verify.
Is Figma Context MCP actively maintained?
Actively maintained. The repository was pushed to within the last 4 day(s).
What license does Figma Context MCP use?
Figma Context MCP ships under MIT. A declared, OSI-approved license is one of the transparency signals HVTrust scores.
Are Figma Context MCP's commits signed?
82% of the last 100 commits to Figma Context MCP are verified-signed (GPG, SSH, S/MIME, or GitHub's signing flow). Signed commits help confirm that code was authored by who the commit claims.
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
Profile context only
HVTrust currently ranks supply-chain and project-integrity trust only. This public view shows a compact AI-agent surface snapshot from repo docs and manifests. These fields are descriptive context and do not affect the production HVTrust rank. An experimental local preview remains available in Score Lab →, and the policy boundary is tracked on the roadmap →
MCP Server Support
high confidence
Implemented
Figma Context MCP appears to expose MCP server capabilities.
Detailed evidence is not shown in the public view.
External Service Dependencies
low confidence
None detected
No clear third-party provider dependency detected.
Credential signal:
API keys or service config markers documented.
Tool / Plugin Surface
medium confidence
1 tags
Broad capability areas detected.
code
Detailed evidence is not shown in the public view.
Package Provenance Drift
N/A
No package source configured
Detailed evidence is not shown in the public view.
MCP signal live
External deps live
Tool / plugin surface live
Package provenance drift live
Maintain Figma Context MCP?
HVTrust scores Figma Context MCP 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.
Data sources
GitHub REST API (repo, commits, stars, forks, license)
Each agent's signals refresh once daily across 6 staggered batches. Methodology v3.2 · Raw JSON
