Is Bigquery MCP safe to use?

Bigquery MCP has an HVTrust score of 36.5/100 (Grade D), ranked #1272 of 1378 tracked AI agent projects. This score reflects verifiable supply-chain integrity, transparency, maintenance, and adoption signals.

What is the trust score for Bigquery MCP?

Bigquery MCP scores 36.5/100 on HVTracker's evidence-weighted HVTrust scale. It has 10 GitHub stars and is categorized under MCP Servers.

Bigquery MCP

Repository

Website

A MCP server for Google's BigQuery database

MCP Servers Python Listed MIT

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

OSSF Scorecard 2.8 / 10

Provenance None

Signed commits 17%

Last push 203d ago

Advisories None known

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In detail: Bigquery MCP scores 36.5/100 (Grade D), ranked #1272 of 1378 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 2.8/10; 17% of recent commits are signed; no published advisory affects its latest release (sl-bigquery-mcp); last pushed 2026-03-27. Every point is earned from checkable signals — never paid placement. How scoring works →

How Bigquery MCP 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.

Publish build provenance for its packagesPyPI Trusted Publishing attestations +14.7 → 51.2 C · #543 of 781
Raise the OSSF Scorecard from 2.8 to 9.0lowest checks: CII-Best-Practices 0, Contributors 0, Dependency-Update-Tool 0 +13.0 → 49.5 D · #580 of 781
Sign every commit17% signed today +4.2 → 40.7 D · #693 of 781

Already done? Suggest a correction Add the trust badge

Chain of custody

Scanners check what the code says. This traces who ships Bigquery MCP 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.

Source Partly signed

github.com/SnowLeopard-AI/bigquery-mcp, MIT, last pushed 2026-03-27. 17% of the last 100 commits carry a verified signature; the rest can't be tied to a verified identity.
Review and release Weak

OpenSSF Scorecard rates the repository's practices 2.8/10 (scanned Oct 10, 2026). The checks that decide who can get a change released:
- Code Review2
- Branch Protection8
- Signed Releases0
- Dangerous Workflow10
- Token Permissions0
- Pinned Dependencies0
All 18 Scorecard checks

Binary-Artifacts 10

Branch-Protection 8

CI-Tests 2

CII-Best-Practices 0

Code-Review 2

Contributors 0

Dangerous-Workflow 10

Dependency-Update-Tool 0

Fuzzing 0

License 10

Maintained 0

Packaging -1

Pinned-Dependencies 0

SAST 0

Security-Policy 0

Signed-Releases 0

Token-Permissions 0

Vulnerabilities 0
Published packages Linked, not attested
- PyPI sl-bigquery-mcp Source link points back to this repo No build attestation
Without a build attestation, nothing proves the published files were built from this repository.
What you install today No known advisories

Latest release checked: sl-bigquery-mcp 0.1.9. No published advisory affects it (OSV, checked 2026-10-16).

Changes to this chain

2026-08-29 OSSF Scorecard: 2.9/10

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 Bigquery MCP’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.

Signed credential (JSON) How to verify

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 Bigquery MCP compares in MCP Servers

Bars show each HVTrust score; the tick marks Bigquery MCP’s 36.5.

Where the 36.5 comes from

HVTrust dimensions vs the MCP Servers average

36.5 / 100 · 100.0% confidence

Bigquery MCP MCP Servers average (781 agents)

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

4.3 / 25

6.2 below avg 10.5

Identity / Provenance60% listing status · 40% build provenance

10.8 / 18

2.7 below avg 13.5

Transparency50% declared license · 50% OSSF Scorecard

10.9 / 17

1.4 below avg 12.3

Maintenance60% last-push freshness · 40% commit activity

0 / 20

12.3 below avg 12.3

AdoptionLog-scaled stars · package downloads

4.5 / 20

2.9 below avg 7.4

Quick Trust Read

What Would Improve It

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

Recent Changes

2026-10-09

Rank Moved

Rank dropped 13 spots (#1244 → #1257)

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Rank Moved

Rank rose 80 spots (#1302 → #1222)

Maintainer Checklist

Raise Scorecard signals Current OSSF Scorecard is 2.8/10. 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.

Refresh maintenance signals The repo was last pushed 203 days ago. Fresh activity helps separate stable projects from stale ones.

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

7.6

Activity sub-score · out of 100

#735

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 D 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

2026-09-29 2026-10-16

Activity & Reach

Stars

Forks

Last Push

2026-03-27

203 days ago

Commits (4 wk)

Downloads (7d)

pypi

HN mentions (30d)

—

Open Issues

Rank Change

▼3

was #1269

Analysis

Activity Inputs

7.6 / 100

StarsRepository reach

6.2 / 30

FreshnessLast push recency

0.0 / 25

ActivityRecent commits

0.0 / 25

CommunityFork signal

1.4 / 20

Common questions about Bigquery MCP

Public trust evidence for Bigquery 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 Bigquery MCP publish package provenance?

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

Bigquery MCP has an OpenSSF Scorecard score of 2.8/10. 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 Bigquery MCP actively maintained?

Stale. The repository has not been pushed to in 203 days. Consider whether the project is still being maintained.

What license does Bigquery MCP use?

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

Are Bigquery MCP's commits signed?

17% of the last 100 commits to Bigquery 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

high confidence

Implemented

Bigquery MCP appears to expose MCP server capabilities.

Detailed evidence is not shown in the public view.

External Service Dependencies

None detected

No clear third-party provider dependency detected.

Credential signal: No explicit API-key/config marker detected.

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 Bigquery 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 → implemented

Maintain Bigquery MCP?

For maintainers

HVTrust scores Bigquery 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

2026-10-09

Rank Moved

Rank dropped 13 spots (#1244 → #1257)

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Rank Moved

Rank rose 80 spots (#1302 → #1222)

2026-09-23

HVTrust Changed

HVTrust up 23.3pts (12.9 → 36.2)

2026-09-22

Newly Listed

First tracked at rank #1302

2026-09-21

Removed From Active Tracking

Removed from active tracking

2026-09-12

Rank Moved

Rank dropped 11 spots (#1197 → #1208)

2026-09-09

Rank Moved

Rank dropped 15 spots (#1176 → #1191)

2026-09-08

Rank Moved

Rank dropped 16 spots (#1160 → #1176)

2026-09-07

Rank Moved

Rank dropped 17 spots (#1143 → #1160)

2026-09-06

Rank Moved

Rank dropped 16 spots (#1127 → #1143)

2026-09-05

Rank Moved

Rank dropped 31 spots (#1096 → #1127)

2026-09-04

Rank Moved

Rank dropped 21 spots (#1075 → #1096)

2026-09-03

Rank Moved

Rank dropped 59 spots (#1016 → #1075)

2026-09-02

Rank Moved

Rank dropped 49 spots (#967 → #1016)

2026-09-01

Rank Moved

Rank dropped 38 spots (#929 → #967)

2026-08-31

Rank Moved

Rank dropped 31 spots (#898 → #929)

2026-08-30

Rank Moved

Rank dropped 42 spots (#856 → #898)

2026-08-29

Scorecard Added

OSSF Scorecard: 2.9/10

2026-08-29

Rank Moved

Rank rose 187 spots (#1043 → #856)

2026-08-29

HVTrust Changed

HVTrust up 14.9pts (23.5 → 38.4)

2026-08-28

Rank Moved

Rank dropped 35 spots (#1008 → #1043)

2026-08-27

Rank Moved

Rank dropped 26 spots (#982 → #1008)

2026-08-26

Rank Moved

Rank dropped 99 spots (#883 → #982)

2026-08-24

Rank Moved

Rank dropped 14 spots (#872 → #886)

2026-08-19

Rank Moved

Rank dropped 10 spots (#868 → #878)

2026-08-17

Rank Moved

Rank rose 11 spots (#875 → #864)

2026-08-16

Rank Moved

Rank dropped 19 spots (#856 → #875)

2026-08-13

Rank Moved

Rank dropped 11 spots (#845 → #856)

2026-08-10

Rank Moved

Rank dropped 50 spots (#799 → #849)

2026-08-08

Newly Listed

First tracked at rank #791

GitHub → Website → PyPI: sl-bigquery-mcp

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For maintainers

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            [![HVTrust](https://hvtracker.net/badge/bigquery-mcp.svg)](https://hvtracker.net/agents/bigquery-mcp)
            
HTML:
            <a href="https://hvtracker.net/agents/bigquery-mcp"><img src="https://hvtracker.net/badge/bigquery-mcp.svg" alt="HVTrust"></a>

Other agents in MCP Servers

Data sources
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON

Bigquery MCP

How Bigquery MCP could raise its score

Chain of custody

Source Partly signed

Review and release Weak

Published packages Linked, not attested

What you install today No known advisories

Changes to this chain

Evidence behind this score

Verify this score yourself

What this score doesn’t check

How Bigquery MCP compares in MCP Servers

Where the 36.5 comes from

HVTrust dimensions vs the MCP Servers average

Quick Trust Read

Rank Trend

Activity & Reach

Analysis

Activity Inputs

Common questions about Bigquery MCP

AI agent surface

Maintain Bigquery MCP?

Reputation Timeline

Embed Badge Badge guide for maintainers →

Other agents in MCP Servers