Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 00:43 UTC

datalayer / jupyter-mcp-server

🪐 🔧 Model Context Protocol (MCP) Server for Jupyter.

Python · Jupyter NotebookBSD-3-Clause★ 1,276 stars⑂ 195 forkssince Feb 2025View on GitHub ↗
KindCommand-line toolMCP serverLibraryNetwork servicehow this is determined

datalayer/jupyter-mcp-server holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on Security (58/100). It was last updated today. 2 contributors account for most of its recent work.

94
overall / 100
Exceptional

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.

94
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 81 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

DatalayerOrganization
126 followers45 public repossince Jul 2013

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIjupyter_mcp_server2.1.1290,957830 days agojupyter

Metrics by category

Vitality

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

93Exceptional · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
24.9/36Commit cadence — 36/52 weeks with commits
18/18Commit volume — 269 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year269
human_commit_share0.99
days_since_last_push0
active_weeks_last_year36

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 56 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~1.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count56
latest_release_tagv2.1.12
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases1.6
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?

80Excellent · 17% of overall
How it's scored
50.4/60Stars — 1,276 stars
19.1/25Forks — 195 forks
5.8/15Watchers — 12 watchers
Inputs used
forks195
stars1,276
watchers12
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (BSD-3-Clause)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges15
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
66.1/80Monthly downloads — 90,957 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesjupyter_mcp_server
dependents—
ecosystemspypi
total_downloads—
monthly_downloads90,957
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?

75Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13.7/22.5Commit distribution — top contributor authored 39% of commits
13.5/13.5Contributor breadth — 43 contributors
10/10OpenSSF Scorecard: Contributors — project has 11 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled43
top_contributor_share0.393
How it's scored
34.3/42Issue resolution — 82% of issues closed
26.6/30PR acceptance — 241/272 decided PRs merged
12.3/13Newcomer PR acceptance — 18/19 first-time contributors' PRs merged in 30d
3/15OpenSSF Scorecard: Code-Review — Found 8/29 approved changesets -- score normalized to 2
Inputs used
merged_prs241
open_issues30
closed_issues133
prs_merged_7d14
prs_decided_7d14
prs_merged_30d55
prs_decided_30d57
issue_closed_ratio0.816
closed_unmerged_prs31
first_time_authors_30d9
first_time_prs_merged_30d18
first_time_prs_decided_30d19
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
15.1/25Owner reach — 126 followers of datalayer
24.1/25Track record — 45 public repos, account ~13 yr old
Inputs used
followers126
owner_typeOrganization
is_verifiedno
owner_logindatalayer
public_repos45
account_age_days4,805

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 — 83 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesjupyter_mcp_server
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows — 6 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 — 16 out of 16 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

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://jupyter-mcp-server.datalayer.tech
10/10Repository description
10/10Topics — 5 topics
10/10Wiki
Inputs used
topicsjupyter, mcp-server, ai, mcp, tools
has_wikiyes
homepagehttps://jupyter-mcp-server.datalayer.tech
docs_sitehttps://jupyter-mcp-server.datalayer.tech
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

58Moderate · 16% of overall
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 — 16 out of 16 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
1.5/7.5Code-Review — Found 8/29 approved changesets -- score normalized to 2
2.5/2.5Contributors — project has 11 contributing companies or organizations
0/10Dangerous-Workflow — 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 10 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
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not 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_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.7
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
advisories0
affected_packages0
assessed_packages4
unassessed_packages39
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 4 resolved dependencies against OSV. 39 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. 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.

74Good · 4% of overall
How it's scored
45/45Agent instructions — .github/copilot-instructions.md, extensions/prompt-templates/general/AGENT.md, extensions/prompt-templates/notebook-review/AGENT.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 95 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.96
agent_instruction_files.github/copilot-instructions.md, extensions/prompt-templates/general/AGENT.md, extensions/prompt-templates/notebook-review/AGENT.md
agent_instruction_max_bytes9,221
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile, examples/cli/Makefile, extensions/sandboxes/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — Dockerfile
10/10Demonstrated agent practice — 17 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 1 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
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile, docs/Makefile, examples/cli/Makefile, extensions/sandboxes/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.17
toolchain_manifests—
dependency_bot_commit_share0.01
How it's scored
0/45Type-checkable code — Python without a type-check config
54.4/55Manageable file sizes — 2/190 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes89,621
source_files_sampled190
oversized_source_files2
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
20/20MCP server
40/40Runnable examples — examples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalyes
api_schema_files—
interfaces_expected_ofnetwork-service

Key facts

1,276GitHub stars
43contributors
269commits, last 12 months
0days since last push
56releases
2bus factor
30open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:jupyter_mcp_server@2.1.12; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 195 ⇿
0Stars
195Forks
51Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

04080120160200191212025-032025-122026-09
Major 2Minor 12Patch 37

Each point covers 2 days.

OpenSSF Scorecard 4.7 / 10
4.7aggregate

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 00:43 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests16 out of 16 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 8/29 approved changesets -- score normalized to 2
10Contributorsproject has 11 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 10 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
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 15
RegistryPackageVersion constraintManifest
PyPIcode-sandboxes>=1.1.2pyproject.toml
PyPIdatalayer-reactor—pyproject.toml
PyPIjupyter-nbmodel-client>=1.5.1pyproject.toml
PyPIjupyter-server-nbmodel>=0.2.8pyproject.toml
PyPIjupyter-server-client>=0.1.1pyproject.toml
PyPIjupyter_server>=2.10,<3pyproject.toml
PyPIjupyter-collaboration>=5pyproject.toml
PyPImcp>=2,<3pyproject.toml
PyPIpycrdt>=0.14.3pyproject.toml
PyPIpydantic—pyproject.toml
PyPIuvicorn—pyproject.toml
PyPItyper—pyproject.toml
PyPIfastapi—pyproject.toml
PyPIopentelemetry-api>=1.24.0pyproject.toml
PyPIopentelemetry-sdk>=1.24.0pyproject.toml
All dependencies 43

Full resolved dependency set from the GitHub dependency graph: 10 direct and 33 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcode-sandboxes—direct
PyPIjupyter-collaboration—direct
PyPIjupyter-nbmodel-client—direct
PyPIjupyter-server—direct
PyPIjupyter-server-client—direct
PyPIjupyter-server-nbmodel—direct
PyPImcp—direct
PyPIopentelemetry-api—direct
PyPIopentelemetry-sdk—direct
PyPIpycrdt—direct
npm@datalayer/icons-react^1.0.0indirect
npm@datalayer/primer-addons^1.0.12indirect
npm@docusaurus/core^3.5.2indirect
npm@docusaurus/preset-classic^3.5.2indirect
npm@docusaurus/theme-live-codeblock^3.5.2indirect
npm@docusaurus/theme-mermaid^3.5.2indirect
npm@mdx-js/react^3.0.1indirect
npm@primer/react-brand^0.58.0indirect
npmclsx^2.1.1indirect
npmdocusaurus-lunr-search^3.5.0indirect
npmmcp-parser0.4.1indirect
npmreact18.3.1indirect
npmreact-calendly^4.1.0indirect
npmreact-dom18.3.1indirect
npmreact-modal-image^2.6.0indirect
npmsourcey3.6.5indirect
PyPIbuild—indirect
PyPIfastmcp-slim—indirect
PyPIhatchling—indirect
PyPIipykernel—indirect
PyPIjupyter-mcp-server—indirect
PyPIjupyter-mcp-tools—indirect
PyPIjupyterlab—indirect
PyPImdformat—indirect
PyPImdformat-gfm—indirect
PyPImypy—indirect
PyPIpillow—indirect
PyPIpydantic-ai—indirect
PyPIpytest—indirect
PyPIpytest-asyncio—indirect
PyPIpytest-timeout—indirect
PyPIsetuptools—indirect
PyPItwine—indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 4 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 39 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

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.

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.