Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 18:14 UTC

khuisman / mcp-gee-sweet

Comprehensive mcp interface for Google Workspace APIs

PythonMIT★ 0 stars⑂ 1 forksince May 2026View on GitHub ↗
KindLibraryCommand-line toolNetwork serviceMCP serverhow this is determined

khuisman/mcp-gee-sweet holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Vitality (89/100) and lowest on Community & Adoption (48/100). It was last updated today. A single contributor accounts for most of its recent work.

83
overall / 100
Excellent

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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

Kevin HuismanPersonal account
1 follower3 public repossince Aug 2012

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
PyPImcp-gee-sweet0.9.05,3431301 day agoai-agentclaudegoogle-calendargoogle-docsgoogle-drivegoogle-sheetsgoogle-workspacemcpmodel-context-protocol

Metrics by category

Vitality

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

89Excellent · 21% of overall

Development activity

81Excellent
How it's scored
36/36Push recency — last push 0 days ago
16.6/36Commit cadence — 24/52 weeks with commits
18/18Commit volume — 592 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 29 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year592
human_commit_share0.91
days_since_last_push0
active_weeks_last_year24

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 4 releases published
36/36Release recency — latest release 1 days ago
27/27Release cadence — a release every ~26.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count4
latest_release_tagv0.9.0
releases_from_tagsno
days_since_latest_release1
mean_days_between_releases26.5
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?

48Weak · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 0 stars
0/25Forks — 1 forks
0/15Watchers — 0 watchers
Inputs used
forks1
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_badges1
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

62Moderate
How it's scored
49.7/80Monthly downloads — 5,343 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmcp-gee-sweet
dependents—
ecosystemspypi
total_downloads—
monthly_downloads5,343
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?

53Moderate · 23% of overall

Maintainer resilience (bus factor)

24At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
1/22.5Commit distribution — top contributor authored 95% of commits
13.5/13.5Contributor breadth — 17 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled17
top_contributor_share0.954

Issue & PR responsiveness

66Good
How it's scored
27.5/42Issue resolution — 66% of issues closed
29.5/30PR acceptance — 346/352 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/25 approved changesets -- score normalized to 0
Inputs used
merged_prs346
open_issues128
closed_issues243
prs_merged_7d18
prs_decided_7d18
prs_merged_30d50
prs_decided_30d51
issue_closed_ratio0.655
closed_unmerged_prs6
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

36Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
2.2/25Owner reach — 1 followers of khuisman
16.4/25Track record — 3 public repos, account ~14 yr old
Inputs used
followers1
owner_typeUser
is_verified—
owner_loginkhuisman
public_repos3
account_age_days5,123
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 1 days ago
20/20Version history — 130 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmcp-gee-sweet
ecosystemspypi
any_deprecatedno
min_days_since_publish1

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 14 out of 14 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

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?

70Good · 16% of overall

Security posture

63Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 14 out of 14 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 0/25 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
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 29 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
2/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.3
Excluded from scoring (no data or not applicable): Branch-Protection, 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
advisories0
affected_packages0
assessed_packages96
unassessed_packages0
affected_by_severitynone
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 96 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.

76Good · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 91 of 91 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes80,582

Verify loop (build / test / typecheck)

90Excellent
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — pyrightconfig.json
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 73 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 9 of the last 100 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_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configspyrightconfig.json
agent_commit_share0.73
toolchain_manifests—
dependency_bot_commit_share0.09

Code legibility for models

76Good
How it's scored
27/45Type-checkable code — Python with type-check config (pyrightconfig.json)
48.6/55Manageable file sizes — 8/69 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes141,411
source_files_sampled69
oversized_source_files8

Machine-readable interfaces

20At Risk
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
20/20MCP server
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalyes
api_schema_files—
interfaces_expected_ofnetwork-service

Key facts

0GitHub stars
17contributors
592commits, last 12 months
0days since last push
4releases
1bus factor
128open issues
PyPIpackage ecosystems

Data collection warnings

  • deps.dev does not index pypi:mcp-gee-sweet@0.9.0; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 6.3 / 10
6.3aggregate

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 · 2026-09-10 18:14 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests14 out of 14 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 0/25 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 29 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
4Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 11
RegistryPackageVersion constraintManifest
PyPImcp>=2.0.0pyproject.toml
PyPIgoogle-auth>=2.57.0pyproject.toml
PyPIgoogle-auth-oauthlib>=1.4.1pyproject.toml
PyPIgoogle-api-python-client>=2.199.0pyproject.toml
PyPImarkdown>=3.10.3pyproject.toml
PyPIopenpyxl>=3.1.5pyproject.toml
PyPIPillow>=11.0.0pyproject.toml
PyPIstarlette>=1.6.0pyproject.toml
PyPIcryptography>=50.0.1pyproject.toml
PyPIpython-multipart>=0.0.31pyproject.toml
PyPIpython-dotenv>=1.2.3pyproject.toml
All dependencies 96

Full resolved dependency set from the GitHub dependency graph: 11 direct and 85 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcryptography50.0.1direct
PyPIgoogle-api-python-client2.199.0direct
PyPIgoogle-auth2.57.0direct
PyPIgoogle-auth-oauthlib1.4.1direct
PyPImarkdown3.10.3direct
PyPImcp2.0.0direct
PyPIopenpyxl3.1.5direct
PyPIpillow12.3.0direct
PyPIpython-dotenv1.2.3direct
PyPIpython-multipart0.0.32direct
PyPIstarlette1.6.0direct
PyPIannotated-types0.7.0indirect
PyPIanyio4.13.0indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbackports-asyncio-runner1.2.0indirect
PyPIbackrefs7.0indirect
PyPIcertifi2026.5.20indirect
PyPIcffi2.0.0indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.4.7indirect
PyPIclick8.4.1indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.14.0indirect
PyPIdistlib0.4.0indirect
PyPIet-xmlfile2.0.0indirect
PyPIexceptiongroup1.3.1indirect
PyPIfilelock3.29.0indirect
PyPIghp-import2.1.0indirect
PyPIgoogle-api-core2.30.3indirect
PyPIgoogle-auth-httplib20.4.0indirect
PyPIgoogleapis-common-protos1.75.0indirect
PyPIh110.16.0indirect
PyPIhttpcore22.12.0indirect
PyPIhttplib20.32.0indirect
PyPIhttpx22.12.0indirect
PyPIhttpx2-jsfetch1.0indirect
PyPIidentify2.6.19indirect
PyPIidna3.19indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPImarkupsafe3.0.3indirect
PyPImcp-types2.0.0indirect
PyPImergedeep1.3.4indirect
PyPImike2.2.0indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-get-deps0.2.2indirect
PyPImkdocs-material9.7.7indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPInodeenv1.10.0indirect
PyPIoauthlib3.3.1indirect
PyPIopentelemetry-api1.44.0indirect
PyPIpackaging26.2indirect
PyPIpaginate0.5.7indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.9.6indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit4.6.2indirect
PyPIproto-plus1.28.0indirect
PyPIprotobuf7.35.0indirect
PyPIpyasn10.6.4indirect
PyPIpyasn1-modules0.4.2indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.20.0indirect
PyPIpyjwt2.13.0indirect
PyPIpymdown-extensions11.0.1indirect
PyPIpyparsing3.3.2indirect
PyPIpytest9.1.1indirect
PyPIpytest-asyncio1.4.0indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.3.1indirect
PyPIpywin32311indirect
PyPIpyyaml6.0.3indirect
PyPIpyyaml-env-tag1.1indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrequests-oauthlib2.0.0indirect
PyPIrpds-py0.30.0indirect
PyPIruff0.16.5indirect
PyPIsix1.17.0indirect
PyPIsse-starlette3.4.4indirect
PyPItomli2.4.1indirect
PyPItruststore0.10.4indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPIuritemplate4.2.0indirect
PyPIurllib32.7.0indirect
PyPIuvicorn0.47.0indirect
PyPIverspec0.1.0indirect
PyPIvirtualenv21.3.3indirect
PyPIwatchdog6.0.0indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 96 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct.

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

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Related records

Inspected repositories sharing catalogue tags or ecosystems with khuisman/mcp-gee-sweet. Read them side by side →

95zereight/gitlab-mcpFirst gitlab mcp for you, building togetherExceptional93OpenByteInc/QuantDingerAI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-tradingExceptional92mozilla/firefox-devtools-mcpModel Context Protocol server for Firefox DevTools - enables AI assistants to inspect and control Firefox browser through the Remote Debugging ProtocolExcellent95dbt-labs/dbt-mcpA MCP (Model Context Protocol) server for interacting with dbt.Exceptional94jgravelle/jcodemunch-mcpCut AI token costs 95%+ on code exploration. The leading MCP server for precise, symbol-level GitHub code retrieval via tree-sitter AST. Works with Claude Code, Cursor & any MCP client. 313B+ tokens saved.Exceptional94homeassistant-ai/ha-mcpThe Unofficial and Awesome Home Assistant MCP ServerExceptional

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.