Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-12 20:12 UTC

musharna / data-aggregator-mcp

Unified research-data acquisition MCP — search & fetch datasets across Zenodo, DataCite, NCBI omics (GEO/SRA/BioProject), and literature (PubMed/OpenAIRE) behind one normalized model.

PythonMIT★ 4 stars⑂ 0 forkssince May 2026View on GitHub ↗
KindCommand-line toolMCP serverLibraryhow this is determined
#bioinformatics#datacite#datasets#mcp#model-context-protocol#ncbi#pubmed#python#research-data#zenodo#data-discovery#mcp-server#open-science

musharna/data-aggregator-mcp holds a health index of 86 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Sustainability & Governance (51/100). It was last updated today. A single contributor accounts for most of its recent work.

86
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.

86
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 72 is calibrated to 86 on the published index scale (record calibration 2026-08-02).

Ownership

Jaret ArnoldPersonal account
5 followers42 public repossince Dec 2021Virginia Tech

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
PyPIdata-aggregator-mcp0.70.017,008790 days agobioinformaticsdatacitedatasetsgeomcpmodel-context-protocolncbiresearch-datasrazenodo

Metrics by category

Vitality

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

84Excellent · 21% of overall

Development activity

74Good
How it's scored
36/36Push recency — last push 0 days ago
10.4/36Commit cadence — 15/52 weeks with commits
18/18Commit volume — 1,123 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,123
human_commit_share0.99
days_since_last_push0
active_weeks_last_year15

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 80 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~0.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count80
latest_release_tagv0.71.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases0.7
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?

53Moderate · 17% of overall

Popularity & adoption

8Critical
How it's scored
7.7/60Stars — 4 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars4
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_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

70Good
How it's scored
56.4/80Monthly downloads — 17,008 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdata-aggregator-mcp
dependents—
ecosystemspypi
total_downloads—
monthly_downloads17,008
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?

51Moderate · 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

62Moderate
How it's scored
25.2/42Issue resolution — 60% of issues closed
29.1/30PR acceptance — 268/276 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/7 approved changesets -- score normalized to 0
Inputs used
merged_prs268
open_issues2
closed_issues3
prs_merged_7d33
prs_decided_7d34
prs_merged_30d58
prs_decided_30d59
issue_closed_ratio0.6
closed_unmerged_prs8
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

46Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
5.6/25Owner reach — 5 followers of musharna
21.5/25Track record — 42 public repos, account ~4 yr old
Inputs used
followers5
owner_typeUser
is_verified—
owner_loginmusharna
public_repos42
account_age_days1,758
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 — 79 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdata-aggregator-mcp
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows — 8 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 8 out of 8 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://musharna.github.io/projects/MCPServers/
10/10Repository description
10/10Topics — 13 topics
0/10Wiki
Inputs used
topicsbioinformatics, datacite, datasets, mcp, model-context-protocol, ncbi, pubmed, python, research-data, zenodo, data-discovery, mcp-server, open-science
has_wikino
homepagehttps://musharna.github.io/projects/MCPServers/
docs_sitehttps://musharna.github.io/projects/MCPServers/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

76Good · 16% of overall

Security posture

70Good
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 — 8 out of 8 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 0/7 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
7.5/7.5Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
5/5Pinned-Dependencies — all dependencies are pinned
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_aggregate7
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_packages94
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 94 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.

73Good · 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 — 97 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.98
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes3,551

Verify loop (build / test / typecheck)

61Moderate
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 agent-authored commits among the last 100
8/8Automated maintenance — 1 of the last 100 commits are automated dependency updates
10/10OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.01

Code legibility for models

54Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
54.5/55Manageable file sizes — 3/313 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes96,990
source_files_sampled313
oversized_source_files3

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
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

4GitHub stars
1contributors
1,123commits, last 12 months
0days since last push
80releases
1bus factor
2open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:data-aggregator-mcp@0.70.0; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 7.0 / 10
7.0aggregate

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 · 2026-10-12 20:12 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-Tests8 out of 8 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 0/7 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
10Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
10Pinned-Dependenciesall dependencies are pinned
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 4
RegistryPackageVersion constraintManifest
PyPImcp>=2,<3pyproject.toml
PyPIhttpx>=0.27pyproject.toml
PyPIpydantic>=2.6pyproject.toml
PyPIdefusedxml>=0.7pyproject.toml
All dependencies 94

Full resolved dependency set from the GitHub dependency graph: 4 direct and 90 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIdefusedxml0.7.1direct
PyPIhttpx0.28.1direct
PyPImcp2.2.0direct
PyPIpydantic2.13.4direct
PyPIaiohappyeyeballs2.6.2indirect
PyPIaiohttp3.14.3indirect
PyPIaiosignal1.4.0indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.14.2indirect
PyPIast-serialize0.5.0indirect
PyPIattrs26.1.0indirect
PyPIcachetools7.2.0indirect
PyPIcattrs26.2.1indirect
PyPIcertifi2026.5.20indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.5.2indirect
PyPIclick8.4.1indirect
PyPIcolorama0.4.6indirect
PyPIcolorlog6.12.0indirect
PyPIcoverage7.14.1indirect
PyPIcryptography50.0.0indirect
PyPIdata-aggregator-mcp0.71.0indirect
PyPIduckdb1.5.3indirect
PyPIenum-tools0.12.0indirect
PyPIfrozendict2.4.7indirect
PyPIfrozenlist1.8.0indirect
PyPIfsspec2026.9.0indirect
PyPIh110.16.0indirect
PyPIhtml5rdf1.2.1indirect
PyPIhttpcore1.0.9indirect
PyPIhttpcore22.13.0indirect
PyPIhttpx22.13.0indirect
PyPIhttpx2-jsfetch1.0indirect
PyPIidna3.19indirect
PyPIimportlib-metadata9.0.1indirect
PyPIiniconfig2.3.0indirect
PyPIinquirerpy0.3.4indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIlibrt0.11.0indirect
PyPIlxml6.1.3indirect
PyPImarkdown-it-py4.2.0indirect
PyPImcp-types2.2.0indirect
PyPImdurl0.1.2indirect
PyPImultidict6.9.1indirect
PyPImypy2.1.0indirect
PyPImypy-extensions1.1.0indirect
PyPIopentelemetry-api1.44.0indirect
PyPIowlrl7.6.2indirect
PyPIpackaging26.2indirect
PyPIpathspec1.1.1indirect
PyPIpfzy0.3.4indirect
PyPIplatformdirs4.12.3indirect
PyPIpluggy1.6.0indirect
PyPIprettytable3.18.0indirect
PyPIprompt-toolkit3.0.53indirect
PyPIpropcache0.5.2indirect
PyPIpyarrow24.0.0indirect
PyPIpycparser3.0indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.20.0indirect
PyPIpyjwt2.15.1indirect
PyPIpyld3.3.0indirect
PyPIpyparsing3.3.3indirect
PyPIpyshacl0.40.1indirect
PyPIpytest9.0.3indirect
PyPIpytest-asyncio1.4.0indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-httpx0.36.2indirect
PyPIpython-multipart0.0.31indirect
PyPIpywin32311indirect
PyPIpyyaml6.0.3indirect
PyPIrdflib7.6.0indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrequests-cache1.3.3indirect
PyPIrich13.9.4indirect
PyPIrich-click1.9.9indirect
PyPIroc-validator0.12.1indirect
PyPIrpds-py0.30.0indirect
PyPIruff0.15.14indirect
PyPIsse-starlette3.4.4indirect
PyPIstarlette1.3.1indirect
PyPItoml0.10.2indirect
PyPItomli2.4.1indirect
PyPItruststore0.10.4indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPIurl-normalize3.0.1indirect
PyPIurllib32.8.0indirect
PyPIuvicorn0.48.0indirect
PyPIwcwidth0.9.1indirect
PyPIyarl1.24.2indirect
PyPIzipp4.1.1indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 94 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.

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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.