Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-14 20:29 UTC

ZahiriNatZuke / local-delegate

MCP that delegates mechanical text tasks to a local OpenAI-compatible LLM endpoint to conserve Claude subscription quota.

PythonMIT★ 5 stars⑂ 2 forkssince Jul 2026View on GitHub ↗
KindLibraryCommand-line toolMCP serverNetwork servicehow this is determined
#ai-tools#claude-code#codex#hooks#mcp-server#model-context-protocol#opencode#skills

ZahiriNatZuke/local-delegate holds a health index of 75 out of 100, placing it in the Good band. It scores highest on Engineering Quality (96/100) and lowest on AI Readiness (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

Yohan González AlmaguerPersonal account
22 followers33 public repossince Jul 2018Kernel Shift SAS

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
PyPIlocal-delegate-mcp0.27.01,283375 days agoclaudellama-swapllmlocalmcpollamaopenai-compatiblequota

Metrics by category

Vitality

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

71Good · 21% of overall

Development activity

58Moderate
How it's scored
36/36Push recency — last push 0 days ago
4.2/36Commit cadence — 6/52 weeks with commits
18/18Commit volume — 207 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_year207
human_commit_share0.94
days_since_last_push0
active_weeks_last_year6

Release discipline

90Excellent
How it's scored
27/27Ships releases — 37 releases published
36/36Release recency — latest release 5 days ago
27/27Release cadence — a release every ~4.4 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count37
latest_release_tagv0.27.0
releases_from_tagsno
days_since_latest_release5
mean_days_between_releases4.4

Community & Adoption

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

49Weak · 17% of overall

Popularity & adoption

10Critical
How it's scored
9.8/60Stars — 5 stars
0/25Forks — 2 forks
0/15Watchers — 0 watchers
Inputs used
forks2
stars5
watchers0
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 (MIT)
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_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

52Moderate
How it's scored
41.4/80Monthly downloads — 1,283 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packageslocal-delegate-mcp
dependents—
ecosystemspypi
total_downloads—
monthly_downloads1,283
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?

53Moderate · 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

61Moderate
How it's scored
0/42Issue resolution — no issues or no data
27.4/30PR acceptance — 158/173 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs158
open_issues0
closed_issues0
prs_merged_7d14
prs_decided_7d14
prs_merged_30d23
prs_decided_30d23
issue_closed_ratio—
closed_unmerged_prs15
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

54Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
9.8/25Owner reach — 22 followers of ZahiriNatZuke
23.2/25Track record — 33 public repos, account ~8 yr old
Inputs used
followers22
owner_typeUser
is_verified—
owner_loginZahiriNatZuke
public_repos33
account_age_days2,984
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 5 days ago
20/20Version history — 37 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageslocal-delegate-mcp
ecosystemspypi
any_deprecatedno
min_days_since_publish5

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
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 — 30 out of 30 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://zahirinatzuke.github.io/local-delegate/
10/10Repository description
10/10Topics — 8 topics
10/10Wiki
Inputs used
topicsai-tools, claude-code, codex, hooks, mcp-server, model-context-protocol, opencode, skills
has_wikiyes
homepagehttps://zahirinatzuke.github.io/local-delegate/
docs_sitehttps://zahirinatzuke.github.io/local-delegate/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

61Moderate · 16% of overall

Security posture

51Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 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 0/30 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
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
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_aggregate5.1
Excluded from scoring (no data or not applicable): Packaging. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages32
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:local-delegate-mcp@0.27.0 runtime dependency closure — what installing the published package pulls in — 32 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.

49Weak · 4% of overall

Agent context & guidance

40Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 94 of 94 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

51Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 6 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
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.06

Code legibility for models

53Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
53.2/55Manageable file sizes — 3/93 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes107,800
source_files_sampled93
oversized_source_files3

Machine-readable interfaces

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

Key facts

5GitHub stars
1contributors
207commits, last 12 months
0days since last push
37releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 2 ⇿
0Stars
2Forks
10Releases

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.

111222212026-072026-072026-07
Major 0Minor 5Patch 5
OpenSSF Scorecard 5.1 / 10
5.1aggregate

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 · 2026-09-14 20:29 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 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 0/30 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
n/aPackagingpackaging workflow not 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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPImcp>=2,<3pyproject.toml
PyPIhttpx2>=2.5,<3pyproject.toml
PyPIplatformdirs>=4,<5pyproject.toml
PyPIfastapi>=0.115pyproject.toml
PyPIuvicorn>=0.30pyproject.toml
PyPIfilelock>=3,<4pyproject.toml
All dependencies 53

Full resolved dependency set from the GitHub dependency graph: 6 direct and 47 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIfastapi0.141.1direct
PyPIfilelock3.32.3direct
PyPIhttpx22.12.0direct
PyPImcp2.1.1direct
PyPIplatformdirs4.11.5direct
PyPIuvicorn0.52.4direct
PyPIannotated-doc0.0.4indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.14.1indirect
PyPIattrs26.1.0indirect
PyPIcffi2.1.0indirect
PyPIcfgv3.5.0indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcryptography50.0.0indirect
PyPIdistlib0.4.3indirect
PyPIgreenlet3.5.4indirect
PyPIh110.16.0indirect
PyPIhttpcore22.12.0indirect
PyPIhttpx2-jsfetch1.0indirect
PyPIidentify2.6.19indirect
PyPIidna3.18indirect
PyPIiniconfig2.3.0indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIlocal-delegate-mcp0.27.0indirect
PyPImcp-types2.1.1indirect
PyPInodeenv1.10.0indirect
PyPIopentelemetry-api1.44.0indirect
PyPIpackaging26.2indirect
PyPIplaywright1.62.0indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit4.6.2indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
PyPIpyee13.0.1indirect
PyPIpygments2.20.0indirect
PyPIpyjwt2.13.0indirect
PyPIpytest9.1.1indirect
PyPIpython-discovery1.4.3indirect
PyPIpython-multipart0.0.32indirect
PyPIpywin32312indirect
PyPIpyyaml6.0.3indirect
PyPIreferencing0.37.0indirect
PyPIrpds-py2026.6.3indirect
PyPIruff0.16.4indirect
PyPIsse-starlette3.4.5indirect
PyPIstarlette1.3.1indirect
PyPItruststore0.10.4indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.2indirect
PyPIvirtualenv21.6.0indirect
Dependency advisories 0

Installing pypi:local-delegate-mcp@0.27.0 pulls in 32 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.

Related records

Inspected repositories sharing catalogue tags or ecosystems with ZahiriNatZuke/local-delegate. Read them side by side →

99awslabs/cli-agent-orchestratorMulti-agent orchestration for AI coding CLIs — Claude Code, Kiro, Codex, and more, coordinated in isolated tmux sessionsExceptional97Observal/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.Exceptional95Q00/ouroborosAgent OS: the agent gets smarter on its own. We just hold the line: Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 14 runtimes: Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, Kiro and more.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+ contributorsExceptional96alpic-ai/skybridgeSkybridge is a full-stack TypeScript framework for MCP Apps and ChatGPT Apps. Type-safe. React-powered. Platform-agnostic.Exceptional

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.