Is YouTube Research MCP safe to use?

YouTube Research MCP has an HVTrust score of 51.4/100 (Grade C), ranked #902 of 1325 tracked AI agent projects. This score reflects verifiable supply-chain integrity, transparency, maintenance, and adoption signals.

What is the trust score for YouTube Research MCP?

YouTube Research MCP scores 51.4/100 on HVTracker's evidence-weighted HVTrust scale. It has 21 GitHub stars and is categorized under MCP Servers.

YouTube Research MCP

coyaSONG/youtube-mcp-server

Citation-ready YouTube research for AI agents — transcript search, exact timestamp links, cross-video evidence, and channel intelligence over MCP

MCP Servers JavaScript Listed MIT

Is YouTube Research MCP safe? Thin or incomplete trust evidence. Review carefully before production use.

OSSF Scorecard 4.6 / 10

Provenance None

Signed commits 40%

Last push 5d ago

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In detail: YouTube Research MCP scores 51.4/100 (Grade C), ranked #902 of 1325 tracked open-source AI agent projects, on evidence coverage B (3 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 4.6/10; 40% of recent commits are signed; last pushed 2026-09-21. Every point is earned from checkable signals — never paid placement. How scoring works →

How YouTube Research MCP compares in MCP Servers

#509 IT Glue 51.6 +0.2
#510 Brainstorm MCP 51.6 +0.2
#511 YouTube Research MCP 51.4 this agent
#512 Zscaler Zero Trust Exchange 51.4 ±0
#513 Tomyud1 Godot MCP 51.4 ±0

Bars show each HVTrust score; the tick marks YouTube Research MCP’s 51.4.

Where the 51.4 comes from

HVTrust dimensions vs the MCP Servers average

51.4 / 100 · 100.0% confidence

YouTube Research MCP MCP Servers average (775 agents)

Safety / Integrity50% OSSF Scorecard · 30% provenance · 20% signed commits

7.7 / 25

2.6 below avg 10.3

Identity / Provenance60% listing status · 40% build provenance

10.8 / 18

2.6 below avg 13.4

Transparency50% declared license · 50% OSSF Scorecard

12.4 / 17

in line with avg 12.2

Maintenance60% last-push freshness · 40% commit activity

11.7 / 20

in line with avg 12.0

AdoptionLog-scaled stars · package downloads

5.8 / 20

1.4 below avg 7.2

Quick Trust Read

What Would Improve It

Publish package provenance or release attestations for stronger supply-chain evidence.

Recent Changes

2026-09-25

Rank Moved

Rank dropped 12 spots (#893 → #905)

2026-09-24

Rank Moved

Rank dropped 10 spots (#883 → #893)

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → declared

Maintainer Checklist

Raise Scorecard signals Current OSSF Scorecard is 4.6/10. Tighten the weakest checks to improve public safety evidence.

Publish provenance Add package provenance or release attestations so users can verify where shipped artifacts came from.

Increase signed commits Raise the share of verified-signed commits to make maintainer identity and release history easier to trust.

Compare with another agent Get email alerts for YouTube Research MCP View MCP Servers Report missing data

37.2

Activity sub-score · out of 100

#511

In MCP Servers

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade C 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

2026-08-11 2026-09-26

Activity & Reach

Stars

Forks

Last Push

2026-09-21

5 days ago

Commits (4 wk)

Downloads (7d)

npm

HN mentions (30d)

—

Open Issues

Rank Change

▲3

was #905

Analysis

Activity Inputs

37.2 / 100

StarsRepository reach

8.1 / 30

FreshnessLast push recency

24.3 / 25

ActivityRecent commits

0.0 / 25

CommunityFork signal

4.7 / 20

Supply Chain Trust

Package Provenance

None

No package attestations found

OSSF Scorecard

4.6 / 10

OpenSSF Scorecard · scanned Sep 21, 2026

Signed Commits

40%

of last 100 commits verified

Binary-Artifacts 10

Branch-Protection 3

CI-Tests 10

CII-Best-Practices 0

Code-Review 0

Contributors 0

Dangerous-Workflow 10

Dependency-Update-Tool 10

Fuzzing 0

License 10

Maintained 10

Packaging 10

Pinned-Dependencies 3

SAST 1

Security-Policy 4

Signed-Releases 0

Token-Permissions 0

Vulnerabilities 0

Common questions about YouTube Research MCP

Public trust evidence for YouTube Research 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 YouTube Research MCP publish package provenance?

No published build provenance is currently detected for YouTube Research 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 YouTube Research MCP have an OpenSSF Scorecard?

YouTube Research MCP has an OpenSSF Scorecard score of 4.6/10. The Scorecard checks for branch protection, signed releases, dependency updates, fuzzing, code review, and other supply-chain hygiene items. See the full check breakdown on this page.

Is YouTube Research MCP actively maintained?

Actively maintained. The repository was pushed to within the last 5 day(s).

What license does YouTube Research MCP use?

YouTube Research MCP ships under MIT. A declared, OSI-approved license is one of the transparency signals HVTrust scores.

Are YouTube Research MCP's commits signed?

39% of the last 100 commits to YouTube Research 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

MCP, providers, tool surface

Scored in HVTrust

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 Server Support

medium confidence

Declared

MCP support appears present, but direct server implementation is less certain.

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

None detected

No clear plugin system or broad tool surface detected.

Detailed evidence is not shown in the public view.

Package Provenance Drift

high confidence

Match

Published package metadata matches the tracked repo

Detailed evidence is not shown in the public view.

MCP signal live
External deps live
Tool / plugin surface live
Package provenance drift live

How this surface has changed

Detected changes to YouTube Research MCP'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.

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → declared

Maintain YouTube Research MCP?

For maintainers

HVTrust scores YouTube Research 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.

Submit a correction → Add the trust badge

Reputation Timeline

Signal history

2026-09-25

Rank Moved

Rank dropped 12 spots (#893 → #905)

2026-09-24

Rank Moved

Rank dropped 10 spots (#883 → #893)

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → declared

2026-09-23

Grade Changed

Trust grade D → C

2026-09-23

Rank Moved

Rank rose 164 spots (#1047 → #883)

2026-09-23

HVTrust Changed

HVTrust up 28.0pts (23.7 → 51.7)

2026-09-22

Newly Listed

First tracked at rank #1047

2026-09-21

Removed From Active Tracking

Removed from active tracking

2026-09-12

Rank Moved

Rank dropped 12 spots (#874 → #886)

2026-09-11

Rank Moved

Rank dropped 18 spots (#856 → #874)

2026-09-07

Rank Moved

Rank dropped 41 spots (#799 → #840)

2026-09-06

Rank Moved

Rank dropped 11 spots (#788 → #799)

2026-09-05

Rank Moved

Rank dropped 57 spots (#731 → #788)

2026-09-04

Rank Moved

Rank dropped 29 spots (#702 → #731)

2026-09-03

Rank Moved

Rank dropped 37 spots (#665 → #702)

2026-09-02

Grade Changed

Trust grade D → C

2026-09-02

Rank Moved

Rank rose 408 spots (#1073 → #665)

2026-09-02

HVTrust Changed

HVTrust up 18.3pts (33.6 → 51.9)

2026-09-01

Rank Moved

Rank dropped 42 spots (#1031 → #1073)

2026-08-31

Rank Moved

Rank dropped 24 spots (#1007 → #1031)

2026-08-30

Rank Moved

Rank dropped 52 spots (#955 → #1007)

2026-08-29

Rank Moved

Rank dropped 47 spots (#908 → #955)

2026-08-28

Rank Moved

Rank dropped 32 spots (#876 → #908)

2026-08-27

Rank Moved

Rank dropped 27 spots (#849 → #876)

2026-08-26

Scorecard Added

OSSF Scorecard: 4.6/10

2026-08-26

Rank Moved

Rank rose 354 spots (#1203 → #849)

2026-08-26

HVTrust Changed

HVTrust up 15.9pts (17.3 → 33.2)

2026-08-16

Rank Moved

Rank dropped 42 spots (#1159 → #1201)

2026-08-13

Rank Moved

Rank dropped 11 spots (#1148 → #1159)

2026-08-11

Activity Score Changed

Activity score down 7pts (48 → 41)

2026-08-10

Rank Moved

Rank dropped 79 spots (#1035 → #1114)

2026-08-08

Newly Listed

First tracked at rank #1035

GitHub → npm: @coyasong/youtube-mcp-server

Embed Badge Badge guide for maintainers →

For maintainers

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Other agents in MCP Servers

Data sources
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 v4.3 · Raw JSON