Brandsystem MCP — Brand Guidelines for AI
Website
Use existing brand guidelines with AI. Turn websites, PDFs, and Figma into a portable .brand runtime through MCP.
Is Brandsystem MCP — Brand Guidelines for AI safe? Strong public trust posture, backed by multiple independent signals.
Compare Brandsystem MCP — Brand Guidelines for AI
How does it stack up against its MCP Servers neighbours?
Pick any agent to compare →In detail: Brandsystem MCP — Brand Guidelines for AI scores 81.0/100 (Grade A), ranked #165 of 1387 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 7.1/10; 82% of recent commits are signed; no published advisory affects its latest release (@brandsystem/mcp); last pushed 2026-11-10. Every point is earned from checkable signals — never paid placement. How scoring works →
How Brandsystem MCP — Brand Guidelines for AI 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 7.1 to 9.0lowest checks: CII-Best-Practices 0, Code-Review 0, Fuzzing 0 +3.7 → 84.7 A · #40 of 779
- Sign every commit82% signed today +0.9 → 81.9 A · #67 of 779
Chain of custody
Scanners check what the code says. This traces who ships Brandsystem MCP — Brand Guidelines for AI 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 Signed
github.com/Brandcode-Studio/brandsystem-mcp, MIT, last pushed 2026-11-10. 82% of the last 100 commits carry a verified signature, so changes trace to a verified account.
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Review and release Strong
OpenSSF Scorecard rates the repository's practices 7.1/10 (scanned Nov 7, 2026). The checks that decide who can get a change released:
- Code Review0
- Branch Protection3
- Signed Releases0
- Dangerous Workflow10
- Token Permissions10
- Pinned Dependencies10
All 18 Scorecard checks
Binary-Artifacts 10Branch-Protection 3CI-Tests 10CII-Best-Practices 0Code-Review 0Contributors 6Dangerous-Workflow 10Dependency-Update-Tool 10Fuzzing 0License 10Maintained 10Packaging 10Pinned-Dependencies 10SAST 9Security-Policy 10Signed-Releases 0Token-Permissions 10Vulnerabilities 9 -
Published packages Linked and attested
- npm @brandsystem/mcp Source link points back to this repo Build provenance attested
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What you install today No known advisories
Latest release checked: @brandsystem/mcp 0.18.0. No published advisory affects it (OSV, checked 2026-11-11).
Changes to this chain
- 2026-09-23 Package provenance attestation detected
- 2026-09-03 OSSF Scorecard: 7.3/10
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 Brandsystem MCP — Brand Guidelines for AI’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 Brandsystem MCP — Brand Guidelines for AI compares in MCP Servers
- #79 Wireshark MCP 81.1 +0.1
- #80 Notion MCP Server 81.1 +0.1
- #81 Brandsystem MCP — Brand Guidelines for AI 81.0 this agent
- #82 Finopsmcp 80.9 −0.1
- #83 Lotus Wisdom 80.9 −0.1
Bars show each HVTrust score; the tick marks Brandsystem MCP — Brand Guidelines for AI’s 81.0.
Where the 81.0 comes from
HVTrust dimensions vs the MCP Servers average
81.0 / 100 · 100.0% confidenceBrandsystem MCP — Brand Guidelines for AI MCP Servers average (779 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 A 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
53.3 / 100Common questions about Brandsystem MCP — Brand Guidelines for AI
Does Brandsystem MCP — Brand Guidelines for AI publish package provenance?
Does Brandsystem MCP — Brand Guidelines for AI have an OpenSSF Scorecard?
Is Brandsystem MCP — Brand Guidelines for AI actively maintained?
What license does Brandsystem MCP — Brand Guidelines for AI use?
Are Brandsystem MCP — Brand Guidelines for AI'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 →
- browser
- database
- MCP signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Detected changes to Brandsystem MCP — Brand Guidelines for AI'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 Brandsystem MCP — Brand Guidelines for AI?
For maintainers
HVTrust scores Brandsystem MCP — Brand Guidelines for AI 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/brandsystem-mcp-brand-guidelines-for-ai)
<a href="https://hvtracker.net/agents/brandsystem-mcp-brand-guidelines-for-ai"><img src="https://hvtracker.net/badge/brandsystem-mcp-brand-guidelines-for-ai.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