Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-27 11:51 UTC

apiguru-app / agent-kit

PythonMIT★ 0 stars⑂ 0 forkssince Sep 2026View on GitHub ↗
KindLibraryMCP serverCommand-line toolhow this is determined

apiguru-app/agent-kit holds a health index of 39 out of 100, placing it in the Weak band. It scores highest on AI Readiness (63/100) and lowest on Sustainability & Governance (28/100). It was last updated today. A single contributor accounts for most of its recent work.

39
overall / 100
Weak

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.

39
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 43 is calibrated to 39 on the published index scale (record calibration 2026-08-02).

Ownership

apiguru-appPersonal account
0 followers3 public repossince Oct 2025

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
npmapiguru-mcp1.1.314,318290 days agomcpmodel-context-protocolmodelcontextprotocolmcp-serveramazonecommerceproduct-datascrapingx402agentclaudecursorcodex
PyPIapiguru-mcp1.1.313,707330 days agoagentamazonecommercemcpmodel-context-protocolscrapingx402

Metrics by category

Vitality

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

50Moderate · 21% of overall

Development activity

36Weak
How it's scored
36/36Push recency — last push 0 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 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_year0
human_commit_share—
days_since_last_push0
active_weeks_last_year0

Release discipline

72Good
How it's scored
16.2/27Ships releases — 1 version tags (no GitHub releases)
36/36Release recency — latest release 0 days ago
12.6/27Release cadence — cadence unknown (single release)
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count1
latest_release_tagv1.1.31
releases_from_tagsyes
days_since_latest_release0
mean_days_between_releases—
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?

34At Risk · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 0 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars0
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

65Good
How it's scored
52.1/80Monthly downloads — 8,025 downloads/month across npm, pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesapiguru-mcp, apiguru-mcp
dependents—
ecosystemsnpm, pypi
total_downloads—
monthly_downloads8,025
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?

28At Risk · 23% of overall

Maintainer resilience (bus factor)

10Critical
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
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1

Issue & PR responsiveness

1Critical
How it's scored
0/42Issue resolution — no issues or no data
0/30PR acceptance — no decided pull requests or no data
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/1 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio—
closed_unmerged_prs0
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, PR acceptance, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

20At Risk
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
0/25Owner reach — 0 followers of apiguru-app
6.3/25Track record — 3 public repos, account ~0 yr old
Inputs used
followers0
owner_typeUser
is_verified—
owner_loginapiguru-app
public_repos3
account_age_days342
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 2 package(s) on npm, pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 33 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesapiguru-mcp, apiguru-mcp
ecosystemsnpm, pypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

58Moderate · 19% of overall

Engineering practices

60Moderate
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

55Moderate
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://dash.apiguru.app/docs
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_sitehttps://dash.apiguru.app/docs
has_readmeyes
has_docs_dirno
has_descriptionno

Security

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

42Weak · 16% of overall

Security posture

42Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/1 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no 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
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — no SAST tool detected
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.2
Excluded from scoring (no data or not applicable): CI-Tests, Signed-Releases. Remaining weights renormalized.

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.

63Moderate · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — GEMINI.md
15/15Machine-readable docs (llms.txt) — llms.txt present
0/40Legible commit history — no data
Inputs used
has_llms_txtyes
llms_txt_url—
legible_history_share—
agent_instruction_filesGEMINI.md
agent_instruction_max_bytes665
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

39Weak
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
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_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/20 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes51,831
source_files_sampled20
oversized_source_files0

Machine-readable interfaces

60Moderate
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — spec/openapi.json, spec/openapi.yaml
20/20MCP server
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalyes
api_schema_filesspec/openapi.json, spec/openapi.yaml
interfaces_expected_of—

Key facts

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

Data collection warnings

  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index npm:apiguru-mcp@1.1.31; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 4.2 / 10
4.2aggregate

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 · 2026-09-27 11:51 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/1 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update 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
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPImcp>=2.0.0mcp/pyproject.toml
PyPIhttpx>=0.27mcp/pyproject.toml
PyPIpydantic>=2.7mcp/pyproject.toml
npm@modelcontextprotocol/sdk^1.30.0npm/package.json
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

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.

Related records

Inspected repositories sharing catalogue tags or ecosystems with apiguru-app/agent-kit. Read them side by side →

94jgravelle/jcodemunch-mcpCut AI token costs 95%+ on code exploration. The leading MCP server for precise, symbol-level GitHub code retrieval via tree-sitter AST. Works with Claude Code, Cursor & any MCP client. 313B+ tokens saved.Exceptional95zereight/gitlab-mcpFirst gitlab mcp for you, building togetherExceptional96alpic-ai/skybridgeSkybridge is a full-stack TypeScript framework for MCP Apps and ChatGPT Apps. Type-safe. React-powered. Platform-agnostic.Exceptional97Observal/ObservalObserval is self-hosted registry for your coding agent extensions with a built in insight engine. Setup Observal, define the scope and share your Skills, MCPs and Agents with your peers.Exceptional96mcp-use/mcp-useThe fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.Exceptional96diegosouzapw/OmniRouteNever stop coding. Free MIT AI gateway: one endpoint, 352 providers (150+ free), 1200+ models Kimi, Claude, GPT, Gemini, GLM, DeepSeek, MiniMax. Works with Claude Code, Codex, Cursor, OpenCode, Cline & Copilot. Quota-aware auto-fallback, RTK+Caveman compression saves 15-95% tokens, MCP/A2A, Desktop/PWA. Built by 550+ contributorsExceptional

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 — npm, PyPI.