Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 02:53 UTC

CrowdStrike / falcon-mcp

Connect AI agents to CrowdStrike Falcon for automated security analysis and threat hunting

PythonMIT★ 221 stars⑂ 74 forkssince Jun 2025View on GitHub ↗
KindMCP serverLibraryhow this is determined

CrowdStrike/falcon-mcp holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Vitality (94/100) and lowest on AI Readiness (44/100). It was last updated today. 2 contributors account 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

CrowdStrikeOrganization
1,368 followers268 public repossince Sep 2012

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIfalcon-mcp0.14.021,328150 days ago

Metrics by category

Vitality

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

94Exceptional · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
25.6/36Commit cadence37/52 weeks with commits
18/18Commit volume185 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year185
human_commit_share
days_since_last_push0
active_weeks_last_year37

Release discipline

100Exceptional
How it's scored
27/27Ships releases15 releases published
36/36Release recencylatest release 0 days ago
27/27Release cadencea release every ~18.2 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count15
latest_release_tagv0.14.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases18.2
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?

71Good · 17% of overall
How it's scored
38/60Stars221 stars
15.5/25Forks74 forks
5.8/15Watchers12 watchers
Inputs used
forks74
stars221
watchers12
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

83Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
11.6/22.5Commit distributiontop contributor authored 48% of commits
13.5/13.5Contributor breadth24 contributors
10/10OpenSSF Scorecard: Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor2
contributors_sampled24
top_contributor_share0.485
How it's scored
39.5/42Issue resolution94% of issues closed
18/30PR acceptance227/379 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs227
open_issues5
closed_issues80
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.941
closed_unmerged_prs152
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
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
22.5/25Owner reach1,368 followers of CrowdStrike
25/25Track record268 public repos, account ~13 yr old
Inputs used
followers1,368
owner_typeOrganization
is_verified
owner_loginCrowdStrike
public_repos268
account_age_days5,039
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 0 days ago
20/20Version history15 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesfalcon-mcp
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall
How it's scored
24/24CI workflows6 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests29 out of 30 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://developer.crowdstrike.com/falcon-mcp/overview/
10/10Repository description
10/10Topics5 topics
0/10Wiki
Inputs used
topicsai, crowdstrike, falcon, mcp, mcp-server
has_wikino
homepagehttps://developer.crowdstrike.com/falcon-mcp/overview/
docs_sitehttps://developer.crowdstrike.com/falcon-mcp/overview/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

81Excellent · 16% of overall

Security posture

81Excellent
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3.8/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.2/2.5CI-Tests29 out of 30 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Reviewall changesets reviewed
2.5/2.5Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
4/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 8
4/5SASTSAST tool is not run on all commits -- score normalized to 8
2/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
7.5/7.5Token-PermissionsGitHub workflow tokens follow principle of least privilege
5.2/7.5Vulnerabilities3 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate8.1
Excluded from scoring (no data or not applicable): 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.

44Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno data
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile, lockfile
0/10Demonstrated agent practiceno data
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
8/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 8
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/142 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes47,953
source_files_sampled142
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
20/20MCP server
40/40Runnable examplesexamples
Inputs used
example_dirsexamples
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

221GitHub stars
24contributors
185commits, last 12 months
0days since last push
15releases
2bus factor
5open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 8.1 / 10
8.1aggregate

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 · 2026-07-17 02:53 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
9CI-Tests29 out of 30 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
8Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 8
8SASTSAST tool is not run on all commits -- score normalized to 8
4Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
7Vulnerabilities3 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPIcrowdstrike-falconpy>=1.3.0pyproject.toml
PyPImcp>=1.12.1,<2.0.0pyproject.toml
PyPIpython-dotenv>=1.1.1pyproject.toml
All dependencies 61

Full resolved dependency set from the GitHub dependency graph: 3 direct and 58 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcrowdstrike-falconpy1.6.3direct
PyPImcp1.28.0direct
PyPIpython-dotenv1.2.2direct
PyPIannotated-types0.7.0indirect
PyPIanyio4.9.0indirect
PyPIast-serialize0.5.0indirect
PyPIattrs25.3.0indirect
PyPIblack26.5.1indirect
PyPIcertifi2025.4.26indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.2indirect
PyPIclick8.4.1indirect
PyPIcloudpickle3.1.1indirect
PyPIcolorama0.4.6indirect
PyPIcryptography49.0.0indirect
PyPIfalcon-mcpindirect
PyPIfalcon-mcp0.14.0indirect
PyPIgoogle-adkindirect
PyPIgoogle-cloud-aiplatformindirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIhttpx-sse0.4.0indirect
PyPIidna3.18indirect
PyPIiniconfig2.1.0indirect
PyPIjsonschema4.25.0indirect
PyPIjsonschema-specifications2025.4.1indirect
PyPIlibrt0.11.0indirect
PyPImypy2.1.0indirect
PyPImypy-extensions1.1.0indirect
PyPIpackaging24.2indirect
PyPIpathspec1.0.4indirect
PyPIplatformdirs4.3.8indirect
PyPIpluggy1.6.0indirect
PyPIpycparser2.22indirect
PyPIpydantic2.11.5indirect
PyPIpydantic2.11.7indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.33.2indirect
PyPIpydantic-core2.46.4indirect
PyPIpydantic-settings2.9.1indirect
PyPIpygments2.19.1indirect
PyPIpyjwt2.13.0indirect
PyPIpytest9.1.1indirect
PyPIpytest-asyncio1.4.0indirect
PyPIpython-multipart0.0.32indirect
PyPIpytokens0.4.1indirect
PyPIpywin32311indirect
PyPIreferencing0.36.2indirect
PyPIrequests2.34.2indirect
PyPIrpds-py0.26.0indirect
PyPIruff0.15.18indirect
PyPIsniffio1.3.1indirect
PyPIsse-starlette3.4.5indirect
PyPIstarlette1.3.1indirect
PyPItyping-extensions4.14.0indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.1indirect
PyPItyping-inspection0.4.2indirect
PyPIurllib32.7.0indirect
PyPIuvicorn0.34.3indirect
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 v0.11.0 — full methodology · metrics wiki.

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