Public record
Software health reportschema 0.26.0 · metrics 2.10.0 · 2026-07-22 02:08 UTC

jagoff / memo

Persistent semantic memory for AI agents — 100% local on Apple Silicon (MLX) or Linux/Ubuntu (CPU). Markdown source of truth, sqlite-vec + BM25 hybrid search, a codegraph-backed knowledge graph, MCP server + CLI. No cloud, no keys.

PythonMIT★ 7 stars⑂ 2 forkssince May 2026View on GitHub ↗
KindMCP serverCommand-line toolLibraryTerminal interfacehow this is determined
#apple-silicon#claude-code#mcp#mcp-server#memory#mlx#model-context-protocol#obsidian#qwen#rag#sqlite-vec#memo#codegraph#linux#agent-memory#claude#embeddings#knowledge-graph#semantic-memory#ai-agents

jagoff/memo holds a health index of 75 out of 100, placing it in the Good band. It scores highest on Vitality (77/100) and lowest on Sustainability & Governance (49/100). It was last updated today. A single contributor accounts for most of its recent work.

75
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.

75
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 65 is calibrated to 75 on the published index scale (record calibration 2026-08-02).

Ownership

Fer FPersonal account
0 followers37 public repossince Jan 2016Nodok.ai

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
PyPImlx-memo3.10.03,119290 days agoagentsapple-siliconclaudelocal-firstmcpmemorymlxobsidianrag

Metrics by category

Vitality

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

77Good · 21% of overall

Development activity

62Moderate
How it's scored
36/36Push recency — last push 0 days ago
7.6/36Commit cadence — 11/52 weeks with commits
18/18Commit volume — 1,443 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_year1,443
human_commit_share0.96
days_since_last_push0
active_weeks_last_year11

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 30 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~1.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count30
latest_release_tagv3.10.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases1.7
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?

49Weak · 17% of overall

Popularity & adoption

13Critical
How it's scored
12.6/60Stars — 7 stars
0/25Forks — 2 forks
0/15Watchers — 0 watchers
Inputs used
forks2
stars7
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonbelow_threshold

Community health

85Excellent
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
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

58Moderate
How it's scored
46.6/80Monthly downloads — 3,119 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmlx-memo
dependents—
ecosystemspypi
total_downloads—
monthly_downloads3,119
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?

49Weak · 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

58Moderate
How it's scored
0/42Issue resolution — no issues or no data
26.3/30PR acceptance — 50/57 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/16 approved changesets -- score normalized to 0
Inputs used
merged_prs50
open_issues0
closed_issues0
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio—
closed_unmerged_prs7
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

42Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
0/25Owner reach — 0 followers of jagoff
23.5/25Track record — 37 public repos, account ~10 yr old
Inputs used
followers0
owner_typeUser
is_verified—
owner_loginjagoff
public_repos37
account_age_days3,847
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 — 29 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmlx-memo
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

77Good · 19% of overall

Engineering practices

68Good
How it's scored
24/24CI workflows — 10 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-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_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://memo-web-sigma.vercel.app
10/10Repository description
10/10Topics — 20 topics
0/10Wiki
Inputs used
topicsapple-silicon, claude-code, mcp, mcp-server, memory, mlx, model-context-protocol, obsidian, qwen, rag, sqlite-vec, memo, codegraph, linux, agent-memory, claude, embeddings, knowledge-graph, semantic-memory, ai-agents
has_wikino
homepagehttps://memo-web-sigma.vercel.app
docs_sitehttps://memo-web-sigma.vercel.app
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 — 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
0/7.5Code-Review — Found 0/16 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
2.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
6.8/7.5Token-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_aggregate6.9
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
advisories2
affected_packages1
assessed_packages216
unassessed_packages33
affected_by_severitymoderate 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 216 resolved dependencies against OSV. 33 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.

69Good · 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 — 96 of 96 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_bytes24,513

Verify loop (build / test / typecheck)

66Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
11/11Static type checking — editors/vscode/tsconfig.json
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 6 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 4 of the last 100 commits are automated dependency updates
5/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
Inputs used
has_nixno
has_testsyes
lockfilespackage-lock.json, uv.lock
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configseditors/vscode/tsconfig.json
agent_commit_share0.06
toolchain_manifests—
dependency_bot_commit_share0.04

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (editors/vscode/tsconfig.json)
54.8/55Manageable file sizes — 4/898 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes84,786
source_files_sampled898
oversized_source_files4

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

7GitHub stars
1contributors
1,443commits, last 12 months
0days since last push
30releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • deps.dev does not index pypi:mlx-memo@3.10.0; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 7 ★ / 2 ⇿
7Stars
2Forks
20Releases

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.

01345687222026-062026-062026-07
Major 0Minor 2Patch 18
OpenSSF Scorecard 6.9 / 10
6.9aggregate

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 · 2026-07-22 02:08 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-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
0Code-ReviewFound 0/16 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
5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 16
RegistryPackageVersion constraintManifest
PyPIclick>=8.1.7pyproject.toml
PyPIrich>=13.7pyproject.toml
PyPIpydantic>=2.6pyproject.toml
PyPIcryptography>=42.0pyproject.toml
PyPIsqlite-vec>=0.1.9,<0.2pyproject.toml
PyPIfastmcp>=0.5,<4pyproject.toml
PyPIpython-frontmatter>=1.1pyproject.toml
PyPIpyyaml>=6.0pyproject.toml
PyPIquestionary>=2.0pyproject.toml
PyPItextual>=8.2.8,<9pyproject.toml
PyPItomli-w>=1.0pyproject.toml
PyPIwatchdog>=4.0pyproject.toml
PyPImlx>=0.18,<1pyproject.toml
PyPImlx-lm>=0.18pyproject.toml
PyPIsentence-transformers>=3.0pyproject.toml
PyPItransformers<5.13pyproject.toml
All dependencies 249

Full resolved dependency set from the GitHub dependency graph: 32 direct and 217 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPImlx0.32.0direct
PyPImlx-lm—direct
PyPImlx-lm0.31.3direct
PyPIpydantic—direct
PyPIpydantic2.13.4direct
PyPIpython-frontmatter—direct
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PyPIrich15.0.0direct
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PyPIsqlite-vec—direct
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PyPItextual—direct
PyPItextual8.2.8direct
PyPItomli-w—direct
PyPItomli-w1.2.0direct
PyPItransformers—direct
PyPItransformers5.12.1direct
PyPIwatchdog—direct
PyPIwatchdog6.0.0direct
npm@types/node26.1.1indirect
npm@types/vscode1.125.0indirect
npm@typescript/typescript-aix-ppc647.0.2indirect
npm@typescript/typescript-darwin-arm647.0.2indirect
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npm@typescript/typescript-linux-mips64el7.0.2indirect
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npm@typescript/typescript-linux-riscv647.0.2indirect
npm@typescript/typescript-linux-s390x7.0.2indirect
npm@typescript/typescript-linux-x647.0.2indirect
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npm@typescript/typescript-win32-arm647.0.2indirect
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PyPIsix1.17.0indirect
PyPIsounddevice0.5.5indirect
PyPIsse-starlette3.4.5indirect
PyPIstarlette1.3.1indirect
PyPIsympy1.14.0indirect
PyPIsyrupy4.8.0indirect
PyPItantivy—indirect
PyPItantivy0.26.0indirect
PyPIthreadpoolctl3.6.0indirect
PyPItiktoken0.13.0indirect
PyPItokenizers0.22.2indirect
PyPItorch2.13.0indirect
PyPItqdm4.68.4indirect
PyPItriton3.7.1indirect
PyPItruststore0.10.4indirect
PyPItyper0.26.8indirect
PyPItypes-pyyaml—indirect
PyPItypes-pyyaml6.0.12.20260518indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.2indirect
PyPIuc-micro-py2.0.0indirect
PyPIuncalled-for0.3.2indirect
PyPIurllib32.7.0indirect
PyPIuvicorn—indirect
PyPIuvicorn0.51.0indirect
PyPIwatchfiles1.2.0indirect
PyPIwcwidth0.8.2indirect
PyPIwebsockets16.1indirect
PyPIxxhash3.8.1indirect
PyPIyarl1.24.2indirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 216 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 0 are direct. 33 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
pytest8.4.2indirectmoderate29.0.3

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 v0.26.0 — full methodology · metrics wiki.

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