Is GPTMe safe to use?

GPTMe has an HVTrust score of 72.6/100 (Grade B), ranked #112 of 1308 tracked AI agent projects. This score reflects verifiable supply-chain integrity, transparency, maintenance, and adoption signals.

What is the trust score for GPTMe?

GPTMe scores 72.6/100 on HVTracker's evidence-weighted HVTrust scale. It has 4.4k GitHub stars and is categorized under Coding Agents.

GPTMe

gptme/gptme

Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web. Make your own p

Coding Agents Python Grade B Listed MIT

72.6/100

Rank #112 of 1308

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Promising trust profile, but some evidence still deserves review.

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Listing state

Listed

Evidence coverage

Grade A · 4/5 signals

Last push

2026-08-25 · 0d ago

Recent change

No recent signal change

Is GPTMe safe? GPTMe scores 72.6/100 (Grade B), ranked #112 of 1308 tracked open-source AI agent projects, on evidence coverage A (4 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 6.1/10; 100% of recent commits are signed; last pushed 2026-08-25. Every point is earned from checkable signals — never paid placement. How scoring works →

Ranked neighbours in Coding Agents

#9 Open Interpreter — 74.2 (B) → #10 OpenHands — 72.7 (B) → #12 CodeWhale — 71.4 (B) → #13 mini-SWE-agent — 71.2 (B) →

Quick Trust Read

What Would Improve It

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

Recent Changes

2026-08-08

Rank Moved

Rank dropped 14 spots (#100 → #114)

Maintainer Checklist

Raise Scorecard signals Current OSSF Scorecard is 6.1/10. 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.

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84.1

Activity sub-score · out of 100

#11

In Coding Agents

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade B reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage A is separate — it grades how many independent signal types back the score (4 of 5), so a high score on thin evidence stays visible. Full methodology →

Rank Trend

2026-08-11 2026-08-25

Activity & Reach

Stars

4.4k

Forks

411

Last Push

2026-08-25

today

Commits (4 wk)

174

Downloads (7d)

7,302

pypi

HN mentions (30d)

Open Issues

Rank Change

▲7

was #119

Analysis

HVTrust Dimensions vs Coding Agents

72.6 / 100 · 100.0% confidence

GPTMe Coding Agents average (70 agents)

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

12.6 / 25

5.0 above avg 7.6

Identity / Provenance60% listing status · 40% build provenance

10.8 / 18

0.8 below avg 11.6

Transparency50% declared license · 50% OSSF Scorecard

13.7 / 17

2.6 above avg 11.1

Maintenance60% last-push freshness · 40% commit activity

20.0 / 20

5.1 above avg 14.9

AdoptionLog-scaled stars · package downloads

13.9 / 20

1.7 above avg 12.2

Activity Inputs

84.1 / 100

StarsRepository reach

21.9 / 30

FreshnessLast push recency

25.0 / 25

ActivityRecent commits

25 / 25

CommunityFork signal

12.2 / 20

Supply Chain Trust

Package Provenance

None

No package attestations found

OSSF Scorecard

6.1 / 10

OpenSSF Scorecard · scanned Aug 24, 2026

Signed Commits

100%

of last 100 commits verified

Binary-Artifacts 9

Branch-Protection 3

CI-Tests 10

CII-Best-Practices 0

Code-Review 7

Contributors 10

Dangerous-Workflow 10

Dependency-Update-Tool 10

Fuzzing 0

License 10

Maintained 10

Packaging 10

Pinned-Dependencies 1

SAST 1

Security-Policy 10

Signed-Releases 8

Token-Permissions 0

Vulnerabilities 0

Is GPTMe safe?

GPTMe has a mixed signal profile. Some trust indicators are present, others are missing. Whether it is safe for your use case depends on which gaps matter to you — review the breakdown below before adopting in production.

Does GPTMe publish package provenance?

No published build provenance is currently detected for GPTMe. This is common for open-source projects but means consumers cannot independently verify that the package on the registry matches the GitHub source.

Does GPTMe have an OpenSSF Scorecard?

GPTMe has an OpenSSF Scorecard score of 6.1/10. 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 GPTMe actively maintained?

Actively maintained. The repository was pushed to within the last 1 day(s).

What license does GPTMe use?

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

Are GPTMe's commits signed?

100% of the last 100 commits to GPTMe 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

GPTMe appears to expose MCP server capabilities.

Detailed evidence is not shown in the public view.

External Service Dependencies

high confidence

6 detected

Public provider/service dependencies detected.

Credential signal: API keys or service config markers documented.

Tool / Plugin Surface

high confidence

Declared

Declared plugin/integration surface detected.

browser
shell

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

Maintain GPTMe?

For maintainers

HVTrust scores GPTMe 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

2026-08-08

Rank Moved

Rank dropped 14 spots (#100 → #114)

2026-07-13

Rank Moved

Rank dropped 11 spots (#83 → #94)

2026-05-29

HVTrust Changed

HVTrust up 10.0pts (57.1 → 67.1)

2026-05-28

Activity Score Changed

Activity score up 25pts (59 → 84)

GitHub → PyPI: gptme

Embed Badge Badge guide for maintainers →

For maintainers

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Other agents in Coding Agents

Data sources
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OpenSSF Scorecard CLI · Algolia HN Search API
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.3 · Raw JSON