Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-22 03:25 UTC

shigechika / entraadm-mcp

MCP server for Microsoft Entra ID sign-in/audit-log triage (read-only)

PythonMIT★ 0 stars⑂ 0 forkssince Aug 2026View on GitHub ↗
KindCommand-line toolMCP serverLibraryhow this is determined

shigechika/entraadm-mcp holds a health index of 69 out of 100, placing it in the Good band. It scores highest on Engineering Quality (80/100) and lowest on Community & Adoption (47/100). It was last updated today. A single contributor accounts for most of its recent work.

69
overall / 100
Good

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.

69
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 62 is calibrated to 69 on the published index scale (record calibration 2026-08-02).

Ownership

AIKAWA ShigechikaPersonal account
21 followers61 public repossince Apr 2010Nihon University

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
PyPIentraadm-mcp1.4.02,49280 days agoentra-idazure-admicrosoft-graphmcpmodel-context-protocolsecurityaudit

Metrics by category

Vitality

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

71Good · 21% of overall

Development activity

51Moderate
How it's scored
36/36Push recency — last push 0 days ago
3.5/36Commit cadence — 5/52 weeks with commits
11.3/18Commit volume — 17 commits in the last year
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Inputs used
commits_last_year17
human_commit_share—
days_since_last_push0
active_weeks_last_year5

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 8 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~8.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count8
latest_release_tagv1.4.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases8.4
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?

47Weak · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 0 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars0
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateyes

Ecosystem adoption (downloads)

57Moderate
How it's scored
45.3/80Monthly downloads — 2,492 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesentraadm-mcp
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,492
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?

50Moderate · 23% of overall

Maintainer resilience (bus factor)

13Critical
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
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1

Issue & PR responsiveness

49Weak
How it's scored
14/42Issue resolution — 33% of issues closed
28.4/30PR acceptance — 18/19 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/18 approved changesets -- score normalized to 0
Inputs used
merged_prs18
open_issues2
closed_issues1
prs_merged_7d5
prs_decided_7d5
prs_merged_30d15
prs_decided_30d15
issue_closed_ratio0.333
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): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

56Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
9.7/25Owner reach — 21 followers of shigechika
25/25Track record — 61 public repos, account ~16 yr old
Inputs used
followers21
owner_typeUser
is_verified—
owner_loginshigechika
public_repos61
account_age_days6,046
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 8 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesentraadm-mcp
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 7 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 18 out of 18 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

75Good
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

63Moderate · 16% of overall

Security posture

54Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 18 out of 18 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/18 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
2.5/5SAST — SAST tool is not run on all commits -- score normalized to 5
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6.8/7.5Vulnerabilities — 1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.4
Excluded from scoring (no data or not applicable): 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
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories2
affected_packages1
assessed_packages51
unassessed_packages0
affected_by_severityhigh 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 51 resolved dependencies against OSV. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

57Moderate · 4% of overall

Agent context & guidance

75Good
How it's scored
45/45Agent instructions — .github/copilot-instructions.md, CLAUDE.md
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.github/copilot-instructions.md, CLAUDE.md
agent_instruction_max_bytes10,351
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

57Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
8/8Automated maintenance — 1 of the last 19 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share0.053
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.

Code legibility for models

48Weak
How it's scored
0/45Type-checkable code — Python without a type-check config
48.1/55Manageable file sizes — 2/16 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes104,327
source_files_sampled16
oversized_source_files2

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

0GitHub stars
1contributors
17commits, last 12 months
0days since last push
8releases
1bus factor
2open issues
PyPIpackage ecosystems

Data collection warnings

  • deps.dev does not index pypi:entraadm-mcp@1.4.0; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 5.4 / 10
5.4aggregate

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 · 2026-10-22 03:25 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests18 out of 18 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/18 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
5SASTSAST tool is not run on all commits -- score normalized to 5
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
9Vulnerabilities1 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPImcp>=2,<3pyproject.toml
PyPIazure-identity>=1.17pyproject.toml
PyPIhttpx>=0.27pyproject.toml
All dependencies 51

Full resolved dependency set from the GitHub dependency graph: 3 direct and 48 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIazure-identity1.25.3direct
PyPIhttpx0.28.1direct
PyPImcp2.2.0direct
PyPIannotated-types0.8.0indirect
PyPIanyio4.14.2indirect
PyPIattrs26.1.0indirect
PyPIazure-core1.41.0indirect
PyPIcertifi2026.7.22indirect
PyPIcffi2.1.1indirect
PyPIcharset-normalizer3.5.1indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcryptography50.0.0indirect
PyPIexceptiongroup1.3.1indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpcore22.13.1indirect
PyPIhttpx22.13.1indirect
PyPIhttpx2-jsfetch1.0indirect
PyPIidna3.19indirect
PyPIiniconfig2.3.0indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPImcp-types2.2.0indirect
PyPImsal1.37.0indirect
PyPImsal-extensions1.3.1indirect
PyPIopentelemetry-api1.45.0indirect
PyPIpackaging26.3indirect
PyPIpluggy1.6.0indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.21.0indirect
PyPIpyjwt2.15.0indirect
PyPIpytest9.1.1indirect
PyPIpython-multipart0.0.32indirect
PyPIpywin32312indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrespx0.23.1indirect
PyPIrpds-py0.30.0indirect
PyPIrpds-py2026.6.3indirect
PyPIruff0.16.4indirect
PyPIsse-starlette3.4.8indirect
PyPIstarlette1.6.0indirect
PyPItomli2.4.1indirect
PyPItruststore0.10.4indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.4indirect
PyPIurllib32.8.0indirect
PyPIuvicorn0.52.4indirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 51 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 0 are direct.

PackageVersionRelationSeverityAdvisoriesFixed in
certifi2026.7.22indirecthigh22026.10.19

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

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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.