Is SageMath MCP safe to use?

SageMath MCP has an HVTrust score of 87.4/100 (Grade A), ranked #48 of 1343 tracked AI agent projects. This score reflects verifiable supply-chain integrity, transparency, maintenance, and adoption signals.

What is the trust score for SageMath MCP?

SageMath MCP scores 87.4/100 on HVTracker's evidence-weighted HVTrust scale. It has 16 GitHub stars and is categorized under MCP Servers.

SageMath MCP

Repository

Stateful SageMath MCP server: 40 tools for symbolic math, algebra, number theory, graphs, plotting and claim verification. A persistent Sage session per client, an AST policy in front of it, and a hardened container as the real boundary.

MCP Servers Python Listed MIT

Is SageMath MCP safe? Strong public trust posture, backed by multiple independent signals.

OSSF Scorecard 7.9 / 10

Provenance Attested

Signed commits 100%

Last push 2d ago

Advisories None known

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In detail: SageMath MCP scores 87.4/100 (Grade A), ranked #48 of 1343 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 7.9/10; 100% of recent commits are signed; no published advisory affects its latest release (sagemath-mcp); last pushed 2026-09-29. Every point is earned from checkable signals — never paid placement. How scoring works →

How SageMath 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.

Raise the OSSF Scorecard from 7.9 to 9.0lowest checks: Code-Review 0, Fuzzing 0, CII-Best-Practices 2 +1.6 → 89.0 A · #6 of 778

Already done? Suggest a correction Add the trust badge

How SageMath MCP compares in MCP Servers

Bars show each HVTrust score; the tick marks SageMath MCP’s 87.4.

Where the 87.4 comes from

HVTrust dimensions vs the MCP Servers average

87.4 / 100 · 100.0% confidence

SageMath MCP MCP Servers average (778 agents)

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

22.4 / 25

12.1 above avg 10.3

Identity / Provenance60% listing status · 40% build provenance

18.0 / 18

4.6 above avg 13.4

Transparency50% declared license · 50% OSSF Scorecard

15.2 / 17

3.0 above avg 12.2

Maintenance60% last-push freshness · 40% commit activity

19.9 / 20

7.7 above avg 12.2

AdoptionLog-scaled stars · package downloads

6.5 / 20

0.8 below avg 7.3

Quick Trust Read

What Would Improve It

Improve adoption to lift the weakest part of the trust profile.

Recent Changes

2026-09-23

Provider Added

Runtime surface grew — new detected provider dependency: Google Gemini

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Provenance Added

Package provenance attestation detected

Maintainer Checklist

Keep signals current Trust posture is already in a healthy range. The main job is to keep provenance, maintenance, and public evidence fresh.

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58.5

Activity sub-score · out of 100

#14

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 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

2026-09-29 2026-10-01

Activity & Reach

Stars

Forks

Last Push

2026-09-29

2 days ago

Commits (4 wk)

121

Downloads (7d)

432

pypi

HN mentions (30d)

—

Open Issues

Rank Change

was #48

Analysis

Activity Inputs

58.5 / 100

StarsRepository reach

7.4 / 30

FreshnessLast push recency

24.7 / 25

ActivityRecent commits

25 / 25

CommunityFork signal

1.4 / 20

Supply Chain Trust

Package Provenance

Verified

pypi attestation

OSSF Scorecard

7.9 / 10

OpenSSF Scorecard · scanned Sep 29, 2026

Signed Commits

100%

of last 100 commits verified

Binary-Artifacts 10

Branch-Protection 3

CI-Tests 10

CII-Best-Practices 2

Code-Review 0

Contributors 3

Dangerous-Workflow 10

Dependency-Update-Tool 10

Fuzzing 0

License 10

Maintained 10

Packaging 10

Pinned-Dependencies 9

SAST 10

Security-Policy 10

Signed-Releases 10

Token-Permissions 10

Vulnerabilities 10

Common questions about SageMath MCP

Public supply-chain signals for SageMath MCP are strong: it has multiple independent trust indicators in place. This does not replace your own security review, but SageMath MCP carries less obvious unverified-evidence risk than projects with thin signals.

Does SageMath MCP publish package provenance?

Yes. SageMath MCP's package releases carry build provenance attestations, which cryptographically link the published package back to its source repository and CI workflow.

Does SageMath MCP have an OpenSSF Scorecard?

SageMath MCP has an OpenSSF Scorecard score of 7.9/10. 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 SageMath MCP actively maintained?

Actively maintained. The repository was pushed to within the last 2 day(s).

What license does SageMath MCP use?

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

Are SageMath MCP's commits signed?

100% of the last 100 commits to SageMath 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

SageMath MCP appears to expose MCP server capabilities.

Detailed evidence is not shown in the public view.

External Service Dependencies

medium confidence

1 detected

Public provider/service dependencies detected.

Google Gemini

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 SageMath 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

Provider Added

Runtime surface grew — new detected provider dependency: Google Gemini

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Provenance Added

Package provenance attestation detected

2026-09-16

Provider Added

Runtime surface grew — new detected provider dependency: Google Gemini

Maintain SageMath MCP?

For maintainers

HVTrust scores SageMath 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

2026-09-23

Provider Added

Runtime surface grew — new detected provider dependency: Google Gemini

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Provenance Added

Package provenance attestation detected

2026-09-23

Grade Changed

Trust grade D → A

2026-09-23

Rank Moved

Rank rose 569 spots (#626 → #57)

2026-09-23

HVTrust Changed

HVTrust up 53.9pts (32.9 → 86.8)

2026-09-22

Newly Listed

First tracked at rank #626

2026-09-21

Removed From Active Tracking

Removed from active tracking

2026-09-18

Rank Moved

Rank rose 16 spots (#109 → #93)

2026-09-16

Provider Added

Runtime surface grew — new detected provider dependency: Google Gemini

2026-09-16

Rank Moved

Rank rose 18 spots (#128 → #110)

2026-09-15

Grade Changed

Trust grade B → A

2026-09-15

Rank Moved

Rank rose 34 spots (#162 → #128)

2026-09-09

Rank Moved

Rank rose 19 spots (#167 → #148)

2026-09-07

Rank Moved

Rank dropped 10 spots (#153 → #163)

2026-09-06

Rank Moved

Rank rose 14 spots (#167 → #153)

2026-09-05

Rank Moved

Rank dropped 34 spots (#133 → #167)

2026-09-03

Rank Moved

Rank dropped 13 spots (#116 → #129)

2026-09-02

Scorecard Added

OSSF Scorecard: 5.5/10

2026-09-02

Rank Moved

Rank rose 154 spots (#270 → #116)

2026-09-02

HVTrust Changed

HVTrust up 11.5pts (66.3 → 77.8)

2026-08-31

Rank Moved

Rank dropped 28 spots (#239 → #267)

2026-08-29

Rank Moved

Rank dropped 10 spots (#234 → #244)

2026-08-27

Rank Moved

Rank dropped 12 spots (#220 → #232)

2026-08-26

Rank Moved

Rank dropped 17 spots (#203 → #220)

2026-08-24

Rank Moved

Rank dropped 13 spots (#189 → #202)

2026-08-23

Rank Moved

Rank rose 11 spots (#200 → #189)

2026-08-22

Rank Moved

Rank rose 13 spots (#213 → #200)

2026-08-19

Rank Moved

Rank dropped 10 spots (#195 → #205)

2026-08-17

Rank Moved

Rank rose 13 spots (#202 → #189)

2026-08-16

Newly Listed

First tracked at rank #202

GitHub → PyPI: sagemath-mcp

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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