Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-15 06:16 UTC

doobidoo / mcp-memory-service

Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowledge graph + autonomous consolidation.

Python · HTML · JavaScriptApache-2.0★ 2,016 stars⑂ 348 forkssince Dec 2024View on GitHub ↗
KindCommand-line toolLibraryNetwork serviceMCP serverWeb interfacehow this is determined
#mcp#memory#semantic-search#vector-database#claude#vector-storage#sqlite-vec#mcp-server#model-context-protocol#agent-memory#agentic-ai#ai-agents#autogen#crewai#knowledge-graph#langgraph#long-term-memory#multi-agent#open-source#rag

doobidoo/mcp-memory-service holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Vitality (100/100) and lowest on Security (68/100). It was last updated today. A single contributor accounts 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 80 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

Henry KruppPersonal account
150 followers53 public repossince Jul 2013Data Migration International AG

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-memory-service12.0.18,6493360 days agoagent-memoryagentic-aiai-agentsai-assistantai-memoryautogencloudflarecrewaifastapiknowledge-graphlanggraphlong-term-memorymcpmemory-consolidationmodel-context-protocolmulti-agentopen-sourceprivacy-firstragrest-apiself-hostedsemantic-memorysemantic-searchsqlite-vecvector-database

Metrics by category

Vitality

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

100Exceptional · 21% of overall

Development activity

100Exceptional
How it's scored
36/36Push recency — last push 0 days ago
36/36Commit cadence — 52/52 weeks with commits
18/18Commit volume — 2,355 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_year2,355
human_commit_share0.95
days_since_last_push0
active_weeks_last_year52

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~4.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv12.0.1
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases4.4
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?

81Excellent · 17% of overall

Popularity & adoption

81Excellent
How it's scored
53.6/60Stars — 2,016 stars
21.2/25Forks — 348 forks
5.8/15Watchers — 12 watchers
Inputs used
forks348
stars2,016
watchers12
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 (Apache-2.0)
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_badges7
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

66Good
How it's scored
52.5/80Monthly downloads — 8,649 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmcp-memory-service
dependents—
ecosystemspypi
total_downloads—
monthly_downloads8,649
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?

69Good · 23% of overall

Maintainer resilience (bus factor)

36Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
4/22.5Commit distribution — top contributor authored 82% of commits
13.5/13.5Contributor breadth — 97 contributors
10/10OpenSSF Scorecard: Contributors — project has 22 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled97
top_contributor_share0.822

Issue & PR responsiveness

89Excellent
How it's scored
39.8/42Issue resolution — 95% of issues closed
26/30PR acceptance — 853/985 decided PRs merged
10.8/13Newcomer PR acceptance — 5/6 first-time contributors' PRs merged in 30d
12/15OpenSSF Scorecard: Code-Review — Found 24/28 approved changesets -- score normalized to 8
Inputs used
merged_prs853
open_issues26
closed_issues477
prs_merged_7d36
prs_decided_7d37
prs_merged_30d51
prs_decided_30d55
issue_closed_ratio0.948
closed_unmerged_prs132
first_time_authors_30d5
first_time_prs_merged_30d5
first_time_prs_decided_30d6

Ownership & stewardship

63Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
15.7/25Owner reach — 150 followers of doobidoo
24.6/25Track record — 53 public repos, account ~13 yr old
Inputs used
followers150
owner_typeUser
is_verified—
owner_logindoobidoo
public_repos53
account_age_days4,842
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 — 336 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmcp-memory-service
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall

Engineering practices

68Good
How it's scored
24/24CI workflows — 9 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 29 out of 29 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

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://github.com/doobidoo/mcp-memory-service#readme
10/10Repository description
10/10Topics — 20 topics
10/10Wiki
Inputs used
topicsmcp, memory, semantic-search, vector-database, claude, vector-storage, sqlite-vec, mcp-server, model-context-protocol, agent-memory, agentic-ai, ai-agents, autogen, crewai, knowledge-graph, langgraph, long-term-memory, multi-agent, open-source, rag
has_wikiyes
homepage—
docs_sitehttps://github.com/doobidoo/mcp-memory-service#readme
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

68Good · 16% of overall

Security posture

60Moderate
How it's scored
6/7.5Binary-Artifacts — binaries present in source code
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 29 out of 29 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
6/7.5Code-Review — Found 24/28 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 22 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 29 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
2/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
5/5SAST — SAST tool is run on all commits
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_aggregate6
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
advisories3
affected_packages2
assessed_packages249
unassessed_packages17
affected_by_severityhigh 1, moderate 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 249 resolved dependencies against OSV. 17 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.

73Good · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — .claude/directives/agents.md, AGENTS.md, CLAUDE.md, docs/guides/AGENTS.md, docs/integrations/gemini.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 95 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_files.claude/directives/agents.md, AGENTS.md, CLAUDE.md, docs/guides/AGENTS.md, docs/integrations/gemini.md
agent_instruction_max_bytes31,688

Verify loop (build / test / typecheck)

65Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
11/11Static type checking — video/tsconfig.json
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 7 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 5 of the last 100 commits are automated dependency updates
4/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
Inputs used
has_nixno
has_testsyes
lockfilespackage-lock.json, uv.lock
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configsvideo/tsconfig.json
agent_commit_share0.07
toolchain_manifests—
dependency_bot_commit_share0.05

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (video/tsconfig.json)
54/55Manageable file sizes — 17/912 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes762,390
source_files_sampled912
oversized_source_files17

Machine-readable interfaces

60Moderate
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
20/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalyes
api_schema_files—
interfaces_expected_ofnetwork-service

Key facts

2,016GitHub stars
97contributors
2,355commits, last 12 months
0days since last push
100releases
1bus factor
26open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Contributor profile enrichment unavailable: Could not resolve to a User with the login of 'c93fb28650ed15253a95b20b5c4857_AHC'.
  • First-time contributor figures cover 12 of 13 authors (cap 12)
  • Could not fetch npm package 'mcp-memory-video' from its registry
  • deps.dev does not index pypi:mcp-memory-service@12.0.1; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 348 ⇿
0Stars
348Forks
99Releases

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.

0125250375342112024-122025-112026-10
Major 2Minor 49Patch 48

Each point covers 2 days.

OpenSSF Scorecard 6.0 / 10
6.0aggregate

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 · 2026-10-15 06:15 UTC

8Binary-Artifactsbinaries present in source code
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests29 out of 29 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 24/28 approved changesets -- score normalized to 8
10Contributorsproject has 22 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 29 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
9Vulnerabilities1 existing vulnerabilities detected
Direct dependencies 38
RegistryPackageVersion constraintManifest
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All dependencies 266

Full resolved dependency set from the GitHub dependency graph: 38 direct and 228 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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PyPInvidia-nccl-cu132.30.7indirect
PyPInvidia-nvjitlink13.3.33indirect
PyPInvidia-nvshmem-cu133.4.5indirect
PyPInvidia-nvtx13.0.85indirect
PyPIonnx1.22.0indirect
PyPIonnx-ir1.0.0indirect
PyPIonnxruntime1.23.2indirect
PyPIonnxruntime1.24.3indirect
PyPIonnxscript0.7.2indirect
PyPIopentelemetry-api1.44.0indirect
PyPIopentelemetry-exporter-otlp-proto-common1.44.0indirect
PyPIopentelemetry-exporter-otlp-proto-http1.44.0indirect
PyPIopentelemetry-proto1.44.0indirect
PyPIopentelemetry-sdk1.44.0indirect
PyPIopentelemetry-semantic-conventions0.65b0indirect
PyPIorjson3.11.8indirect
PyPIpackaging24.2indirect
PyPIpandas2.3.3indirect
PyPIpandas3.0.2indirect
PyPIpathspec1.0.4indirect
PyPIplatformdirs4.5.1indirect
PyPIpluggy1.6.0indirect
PyPIpropcache0.3.2indirect
PyPIprotobuf6.33.5indirect
PyPIpy-cpuinfo210.1.1indirect
PyPIpyarrow24.0.0indirect
PyPIpycparser2.23indirect
PyPIpydantic2.12.5indirect
PyPIpydantic-core2.41.5indirect
PyPIpydantic-settings2.15.0indirect
PyPIpygments2.20.0indirect
PyPIpymilvus3.0.2indirect
PyPIpyproject-hooks1.2.0indirect
PyPIpyreadline33.5.6indirect
PyPIpytest9.1.1indirect
PyPIpytest-asyncio1.4.0indirect
PyPIpytest-benchmark5.3.0indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-subtests0.15.0indirect
PyPIpytest-timeout2.4.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpytokens0.4.1indirect
PyPIpytz2026.1.post1indirect
PyPIpywin32311indirect
PyPIreferencing0.37.0indirect
PyPIregex2026.7.19indirect
PyPIrich15.0.0indirect
PyPIrpds-py0.30.0indirect
PyPIruff0.17.0indirect
PyPIsafetensors0.8.0indirect
PyPIscikit-learn1.7.2indirect
PyPIscipy1.14.1indirect
PyPIscipy1.17.1indirect
PyPIsentence-transformers5.7.0indirect
PyPIsetuptools81.0.0indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIstarlette1.6.0indirect
PyPIsympy1.14.0indirect
PyPIthreadpoolctl3.5.0indirect
PyPItokenizers0.23.3indirect
PyPItomli2.2.1indirect
PyPItorch2.14.1indirect
PyPItqdm4.67.1indirect
PyPItransformers5.19.0indirect
PyPItriton3.8.0indirect
PyPItruststore0.10.5indirect
PyPItyper0.27.1indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2025.2indirect
PyPItzlocal5.3.1indirect
PyPIurllib32.8.0indirect
PyPIwandb0.30.0indirect
PyPIxxhash4.0.1indirect
PyPIyarl1.25.1indirect
PyPIzipp3.21.0indirect
Dependency advisories 2

This repository publishes no package the index resolves, so its own dependency graph was assessed — 249 packages, which also include development and test pins that never ship: 2 carry known advisories, of which 0 are direct. 17 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
braces3.0.3indirecthigh1—
setuptools81.0.0indirectmoderate283.0.0

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.

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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.