Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 03:20 UTC

langchain-ai / langserve

LangServe 🦜️🏓

JavaScript · Python · TypeScriptCustom license★ 2,330 stars⑂ 272 forkssince Sep 2023archivedView on GitHub ↗
KindLibraryNetwork servicehow this is determined

langchain-ai/langserve holds a health index of 19 out of 100, placing it in the Critical band. It scores highest on Community & Adoption (81/100) and lowest on Vitality (44/100). The repository is archived, so no further maintenance is expected.

19
overall / 100
Critical

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.

19
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 64 is calibrated to 73 on the published index scale (record calibration 2026-08-02).

Ownership

LangChainOrganization
21,624 followers257 public repossince Mar 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIlangserve0.3.3-66299 days ago

Metrics by category

Vitality

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

44Weak · 21% of overall
How it's scored
9.9/36Push recencylast push 99 days ago
6.9/36Commit cadence10/52 weeks with commits
15.7/18Commit volume55 commits in the last year
0/10OpenSSF Scorecard: Maintainedproject is archived
Inputs used
commits_last_year55
human_commit_share0.56
days_since_last_push99
active_weeks_last_year10
How it's scored
27/27Ships releases65 releases published
16.2/36Release recencylatest release 299 days ago
19.8/27Release cadencea release every ~57.5 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count65
latest_release_tagv0.3.3
releases_from_tagsno
days_since_latest_release299
mean_days_between_releases57.5

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

81Excellent · 17% of overall
How it's scored
54.6/60Stars2,330 stars
20.3/25Forks272 forks
7.2/15Watchers21 watchers
Inputs used
forks272
stars2,330
watchers21
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges2
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

67Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
8.6/22.5Commit distributiontop contributor authored 62% of commits
13.5/13.5Contributor breadth27 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled27
top_contributor_share0.62
How it's scored
22.8/42Issue resolution54% of issues closed
27/30PR acceptance450/500 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/2 approved changesets -- score normalized to 0
Inputs used
merged_prs450
open_issues117
closed_issues139
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.543
closed_unmerged_prs50
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.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
25/25Owner reach21,624 followers of langchain-ai
19.9/25Track record257 public repos, account ~3 yr old
Inputs used
followers21,624
owner_typeOrganization
is_verified
owner_loginlangchain-ai
public_repos257
account_age_days1,260
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 299 days ago
20/20Version history66 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packageslangserve
ecosystemspypi
any_deprecatedno
min_days_since_publish299

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 19% of overall
How it's scored
24/24CI workflows7 workflow(s)
24/24Tests present
16/16Linter config.eslintrc.cjs
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests29 out of 29 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics6 topics
10/10Wiki
Inputs used
topicsdeployment, fastapi, langchain, langchain-python, llm, llms
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
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-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests29 out of 29 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/2 approved changesets -- score normalized to 0
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense file detected
0/7.5Maintainedproject is archived
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
5/5SASTSAST tool is run on all commits
5/5Security-Policysecurity policy file detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities76 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): Branch-Protection. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages30
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:langserve@0.3.3 runtime dependency closure — what installing the published package pulls in — 30 packages. 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.

64Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history55 of 56 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.982
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format config.eslintrc.cjs
11/11Static type checkinglangserve/chat_playground/tsconfig.json, langserve/playground/tsconfig.json, langserve/py.typed, libs/langserve-playground/tsconfig.json
10/10Reproducible environmentlockfile
4/10Demonstrated agent practice2 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance44 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock, yarn.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configslangserve/chat_playground/tsconfig.json, langserve/playground/tsconfig.json, langserve/py.typed, libs/langserve-playground/tsconfig.json
agent_commit_share0.02
toolchain_manifests
dependency_bot_commit_share0.44
How it's scored
27/45Type-checkable codeJavaScript with type-check config (langserve/chat_playground/tsconfig.json, langserve/playground/tsconfig.json, langserve/py.typed, libs/langserve-playground/tsconfig.json)
53.3/55Manageable file sizes4/128 source files over 60KB
Inputs used
primary_languageJavaScript
largest_source_bytes367,401
source_files_sampled128
oversized_source_files4
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examplesexamples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files
interfaces_expected_ofnetwork-service

Key facts

2,330GitHub stars
27contributors
55commits, last 12 months
99days since last push
65releases
1bus factor
117open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

More detail

Star and fork history 0 ★ / 272 ⇿
0Stars
272Forks
61Releases

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.

050100150200250300267142023-102025-022026-07
Major 0Minor 3Patch 53

Each point covers 3 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 · 2026-08-13 03:19 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-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
0Code-ReviewFound 0/2 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintainedproject is archived
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities76 existing vulnerabilities detected
Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPIhttpx>=0.23.0,<1.0pyproject.toml
PyPIfastapi>=0.90.1,<1pyproject.toml
PyPIsse-starlette^1.3.0pyproject.toml
PyPIlangchain-core>=0.3,<2pyproject.toml
PyPIorjson>=2,<4pyproject.toml
PyPIpydantic^2.13pyproject.toml
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Dependency advisories 0

Installing pypi:langserve@0.3.3 pulls in 30 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.