Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-08 19:26 UTC

zym9863 / modelscope-image-mcp

A MCP (Model Context Protocol) server for generating images using ModelScope Qwen-Image model.

PythonMIT★ 2 stars⑂ 1 forksince Sep 2025View on GitHub ↗
KindLibraryCommand-line toolMCP serverhow this is determined

zym9863/modelscope-image-mcp holds a health index of 31 out of 100, placing it in the At Risk band. It scores highest on Security (46/100) and lowest on AI Readiness (18/100). It was last updated 166 days ago. A single contributor accounts for most of its recent work.

31
overall / 100
At Risk

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

31
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 37 is calibrated to 31 on the published index scale (record calibration 2026-08-02).

Ownership

zymPersonal account
4 followers409 public repossince Sep 2024

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPImodelscope-image-mcp1.1.0346349 days agoaigenerationimagemcpmodelscopeqwen

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

44Weak · 21% of overall

Development activity

21At Risk
How it's scored
9.9/36Push recency — last push 166 days ago
1.4/36Commit cadence — 2/52 weeks with commits
9.7/18Commit volume — 11 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year11
human_commit_share—
days_since_last_push166
active_weeks_last_year2

Release discipline

78Good
How it's scored
27/27Ships releases — 5 releases published
16.2/36Release recency — latest release 361 days ago
27/27Release cadence — a release every ~0 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count5
latest_release_tagv2.0.3
releases_from_tagsno
days_since_latest_release361
mean_days_between_releases0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

24At Risk · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 2 stars
0/25Forks — 1 forks
0/15Watchers — 0 watchers
Inputs used
forks1
stars2
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

26At Risk
How it's scored
20.6/80Monthly downloads — 34 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmodelscope-image-mcp
dependents—
ecosystemspypi
total_downloads—
monthly_downloads34
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

31At Risk · 23% of overall

Maintainer resilience (bus factor)

10Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1

Issue & PR responsiveness

1Critical
How it's scored
0/42Issue resolution — no issues or no data
0/30PR acceptance — 0/1 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/11 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio—
closed_unmerged_prs1
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

40Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
5/25Owner reach — 4 followers of zym9863
17/25Track record — 409 public repos, account ~1 yr old
Inputs used
followers4
owner_typeUser
is_verified—
owner_loginzym9863
public_repos409
account_age_days726
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

91Excellent
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
26/35Publish recency — latest publish 349 days ago
20/20Version history — 6 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmodelscope-image-mcp
ecosystemspypi
any_deprecatedno
min_days_since_publish349

Engineering Quality

Are baseline engineering and documentation practices in place?

44Weak · 19% of overall

Engineering practices

30At Risk
How it's scored
24/24CI workflows — 1 workflow(s)
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

65Good
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://pypi.org/project/modelscope-image-mcp/
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttps://pypi.org/project/modelscope-image-mcp/
docs_sitehttps://pypi.org/project/modelscope-image-mcp/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

46Weak · 16% of overall

Security posture

33At Risk
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/11 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — no SAST tool detected
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 42 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3.3
Excluded from scoring (no data or not applicable): CI-Tests, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages36
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:modelscope-image-mcp@1.1.0 runtime dependency closure — what installing the published package pulls in — 36 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

18Critical · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

12Critical
How it's scored
0/18One-command bootstrap
0/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsno
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/3 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes16,149
source_files_sampled3
oversized_source_files0

Machine-readable interfaces

33At Risk
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalyes
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

2GitHub stars
1contributors
11commits, last 12 months
166days since last push
5releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

OpenSSF Scorecard 3.3 / 10
3.3aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-08 19:26 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/11 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities42 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPImcp>=1.0.0pyproject.toml
PyPIrequests—pyproject.toml
PyPIpython-dotenv—pyproject.toml
PyPIPillow—pyproject.toml
PyPIhttpx>=0.27.0pyproject.toml
All dependencies 33

Full resolved dependency set from the GitHub dependency graph: 5 direct and 28 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIhttpx0.28.1direct
PyPImcp1.14.0direct
PyPIpillow11.3.0direct
PyPIpython-dotenv1.1.1direct
PyPIrequests2.32.5direct
PyPIannotated-types0.7.0indirect
PyPIanyio4.10.0indirect
PyPIattrs25.3.0indirect
PyPIcertifi2025.8.3indirect
PyPIcharset-normalizer3.4.3indirect
PyPIclick8.2.1indirect
PyPIcolorama0.4.6indirect
PyPIexceptiongroup1.3.0indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx-sse0.4.1indirect
PyPIidna3.10indirect
PyPIjsonschema4.25.1indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIpydantic2.11.7indirect
PyPIpydantic-core2.33.2indirect
PyPIpydantic-settings2.10.1indirect
PyPIpython-multipart0.0.20indirect
PyPIpywin32311indirect
PyPIreferencing0.36.2indirect
PyPIrpds-py0.27.1indirect
PyPIsniffio1.3.1indirect
PyPIsse-starlette3.0.2indirect
PyPIstarlette0.47.3indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.1indirect
PyPIurllib32.5.0indirect
PyPIuvicorn0.35.0indirect
Dependency advisories 0

Installing pypi:modelscope-image-mcp@1.1.0 pulls in 36 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.