Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-20 05:16 UTC

smn2gnt / MCP-Salesforce

MCP Salesforce connector

PythonMIT★ 177 stars⑂ 53 forkssince Dec 2024View on GitHub ↗
KindCommand-line toolMCP serverLibraryhow this is determined
#modelcontextprotocol#salesforce#mcp#server

smn2gnt/MCP-Salesforce holds a health index of 53 out of 100, placing it in the Moderate band. It scores highest on Vitality (65/100) and lowest on AI Readiness (34/100). It was last updated 53 days ago. A single contributor accounts for most of its recent work.

53
overall / 100
Moderate

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.

53
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 52 is calibrated to 53 on the published index scale (record calibration 2026-08-02).

Ownership

SumanPersonal account
3 followers13 public repossince Sep 2013

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-salesforce-connector0.1.185121753 days agollmmcpsalesforce

Metrics by category

Vitality

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

65Good · 21% of overall

Development activity

42Weak
How it's scored
18/36Push recency — last push 53 days ago
4.8/36Commit cadence — 7/52 weeks with commits
14.7/18Commit volume — 42 commits in the last year
4/10OpenSSF Scorecard: Maintained — 4 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 4
Inputs used
commits_last_year42
human_commit_share0.909
days_since_last_push53
active_weeks_last_year7

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 12 releases published
36/36Release recency — latest release 53 days ago
27/27Release cadence — a release every ~39.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count12
latest_release_tagv0.1.18
releases_from_tagsno
days_since_latest_release53
mean_days_between_releases39.4
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?

50Moderate · 17% of overall

Popularity & adoption

53Moderate
How it's scored
36.4/60Stars — 177 stars
14.3/25Forks — 53 forks
2.7/15Watchers — 4 watchers
Inputs used
forks53
stars177
watchers4
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)

45Weak
How it's scored
36.1/80Monthly downloads — 512 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmcp-salesforce-connector
dependents—
ecosystemspypi
total_downloads—
monthly_downloads512
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?

51Moderate · 23% of overall

Maintainer resilience (bus factor)

20At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
2.6/22.5Commit distribution — top contributor authored 89% of commits
8.1/13.5Contributor breadth — 6 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled6
top_contributor_share0.886

Issue & PR responsiveness

56Moderate
How it's scored
28/42Issue resolution — 67% of issues closed
20.5/30PR acceptance — 13/19 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 1/11 approved changesets -- score normalized to 0
Inputs used
merged_prs13
open_issues2
closed_issues4
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.667
closed_unmerged_prs6
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.

Ownership & stewardship

43Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
4.3/25Owner reach — 3 followers of smn2gnt
20.3/25Track record — 13 public repos, account ~13 yr old
Inputs used
followers3
owner_typeUser
is_verified—
owner_loginsmn2gnt
public_repos13
account_age_days4,759
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 53 days ago
20/20Version history — 17 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmcp-salesforce-connector
ecosystemspypi
any_deprecatedno
min_days_since_publish53

Engineering Quality

Are baseline engineering and documentation practices in place?

54Moderate · 19% of overall

Engineering practices

56Moderate
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
8/20OpenSSF Scorecard: CI-Tests — 4 out of 9 merged PRs checked by a CI test -- score normalized to 4
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 4 topics
0/10Wiki
Inputs used
topicsmodelcontextprotocol, salesforce, mcp, server
has_wikino
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?

41Weak · 16% of overall

Security posture

26At Risk
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
1/2.5CI-Tests — 4 out of 9 merged PRs checked by a CI test -- score normalized to 4
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 1/11 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
3/7.5Maintained — 4 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 4
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 44 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate2.6
Excluded from scoring (no data or not applicable): Packaging, 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
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_packages40
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:mcp-salesforce-connector@0.1.18 runtime dependency closure — what installing the published package pulls in — 40 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.

34At Risk · 4% of overall

Agent context & guidance

15Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
15.2/40Legible commit history — 20 of 70 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.286
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

42Weak
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 6 of the last 77 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
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_configno
typecheck_configs—
agent_commit_share0.078
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/4 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes34,286
source_files_sampled4
oversized_source_files0

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

177GitHub stars
6contributors
42commits, last 12 months
53days since last push
12releases
1bus factor
2open 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 ★ / 53 ⇿
0Stars
53Forks
12Releases

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.

01020304050605222025-012025-112026-09
Major 0Minor 0Patch 12

Each point covers 2 days.

OpenSSF Scorecard 2.6 / 10
2.6aggregate

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 · 2026-09-20 05:16 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
4CI-Tests4 out of 9 merged PRs checked by a CI test -- score normalized to 4
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/11 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
4Maintained4 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 4
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities44 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPImcp>=1.0,<2.0pyproject.toml
PyPIsimple-salesforce—pyproject.toml
PyPIpython-dotenv—pyproject.toml
All dependencies 46

Full resolved dependency set from the GitHub dependency graph: 3 direct and 43 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPImcp1.1.2direct
PyPIpython-dotenv1.0.1direct
PyPIsimple-salesforce1.12.6direct
PyPIannotated-types0.7.0indirect
PyPIanyio4.7.0indirect
PyPIattrs24.3.0indirect
PyPIcertifi2024.12.14indirect
PyPIcffi1.17.1indirect
PyPIcharset-normalizer3.4.0indirect
PyPIclick8.1.7indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.13.2indirect
PyPIcryptography44.0.0indirect
PyPIh110.14.0indirect
PyPIhttpcore1.0.7indirect
PyPIhttpx0.28.1indirect
PyPIhttpx-sse0.4.0indirect
PyPIidna3.10indirect
PyPIiniconfig2.3.0indirect
PyPIisodate0.7.2indirect
PyPIlxml5.3.0indirect
PyPImcp-salesforce-connector0.1.18indirect
PyPImore-itertools10.5.0indirect
PyPIpackaging26.0indirect
PyPIplatformdirs4.3.6indirect
PyPIpluggy1.6.0indirect
PyPIpycparser2.22indirect
PyPIpydantic2.10.3indirect
PyPIpydantic-core2.27.1indirect
PyPIpygments2.19.2indirect
PyPIpyjwt2.10.1indirect
PyPIpytest9.0.2indirect
PyPIpytest-asyncio1.3.0indirect
PyPIpytest-cov7.0.0indirect
PyPIpytz2024.2indirect
PyPIrequests2.32.3indirect
PyPIrequests-file2.1.0indirect
PyPIrequests-toolbelt1.0.0indirect
PyPIsniffio1.3.1indirect
PyPIsse-starlette2.1.3indirect
PyPIstarlette0.42.0indirect
PyPItomli2.4.0indirect
PyPItyping-extensions4.12.2indirect
PyPIurllib32.2.3indirect
PyPIuvicorn0.34.0indirect
PyPIzeep4.3.1indirect
Dependency advisories 0

Installing pypi:mcp-salesforce-connector@0.1.18 pulls in 40 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

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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.