Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 10:34 UTC

CrowdStrike / falcon-mcp

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

PythonMIT★ 250 stars⑂ 82 forkssince Jun 2025View on GitHub ↗
KindCommand-line toolMCP serverLibraryhow this is determined
#ai#crowdstrike#falcon#mcp#mcp-server

CrowdStrike/falcon-mcp holds a health index of 95 out of 100, placing it in the Exceptional band. It scores highest on Vitality (94/100) and lowest on AI Readiness (65/100). It was last updated 7 days ago. A single contributor accounts for most of its recent work.

95
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.

95
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 82 is calibrated to 95 on the published index scale (record calibration 2026-08-02).

Ownership

CrowdStrikeOrganization · verified domain
1,421 followers276 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-mcp0.19.047,246217 days ago

Metrics by category

Vitality

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

94Exceptional · 21% of overall

Development activity

90Excellent
How it's scored
36/36Push recency — last push 7 days ago
25.6/36Commit cadence — 37/52 weeks with commits
18/18Commit volume — 176 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year176
human_commit_share0.8
days_since_last_push7
active_weeks_last_year37

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 21 releases published
36/36Release recency — latest release 7 days ago
27/27Release cadence — a release every ~10 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count21
latest_release_tagv0.19.0
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases10
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?

72Good · 17% of overall

Popularity & adoption

61Moderate
How it's scored
38.9/60Stars — 250 stars
15.9/25Forks — 82 forks
5.8/15Watchers — 12 watchers
Inputs used
forks82
stars250
watchers12
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
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
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesbadge.fury.io, shields.io
has_pull_request_templateno

Sustainability & Governance

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

76Good · 23% of overall

Maintainer resilience (bus factor)

37Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
8.2/22.5Commit distribution — top contributor authored 64% of commits
13.5/13.5Contributor breadth — 27 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled27
top_contributor_share0.635

Issue & PR responsiveness

82Excellent
How it's scored
35.2/42Issue resolution — 84% of issues closed
19.1/30PR acceptance — 276/433 decided PRs merged
13/13Newcomer PR acceptance — 4/4 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs276
open_issues21
closed_issues108
prs_merged_7d0
prs_decided_7d0
prs_merged_30d23
prs_decided_30d23
issue_closed_ratio0.837
closed_unmerged_prs157
first_time_authors_30d4
first_time_prs_merged_30d4
first_time_prs_decided_30d4

Ownership & stewardship

98Exceptional
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
22.7/25Owner reach — 1,421 followers of CrowdStrike
25/25Track record — 276 public repos, account ~13 yr old
Inputs used
followers1,421
owner_typeOrganization
is_verifiedyes
owner_loginCrowdStrike
public_repos276
account_age_days5,093

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 7 days ago
20/20Version history — 21 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesfalcon-mcp
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

85Excellent · 19% of overall

Engineering practices

82Excellent
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.black])
0/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 29 out of 30 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://developer.crowdstrike.com/falcon-mcp/overview/
10/10Repository description
10/10Topics — 5 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?

85Excellent · 16% of overall

Security posture

81Excellent
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.2/2.5CI-Tests — 29 out of 30 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
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
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
4/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 8
4/5SAST — SAST tool is not run on all commits -- score normalized to 8
2/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
6.8/7.5Vulnerabilities — 1 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.

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_packages33
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:falcon-mcp@0.19.0 runtime dependency closure — what installing the published package pulls in — 33 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.

65Good · 4% of overall

Agent context & guidance

55Moderate
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://developer.crowdstrike.com/llms.txt)
40/40Legible commit history — 80 of 80 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://developer.crowdstrike.com/llms.txt
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

65Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.black])
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
6/10Demonstrated agent practice — 3 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 10 of the last 100 commits are automated dependency updates
8/10OpenSSF Scorecard: Pinned-Dependencies — dependency 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_configyes
typecheck_configs—
agent_commit_share0.03
toolchain_manifests—
dependency_bot_commit_share0.1

Code legibility for models

53Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
53.2/55Manageable file sizes — 6/184 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes133,289
source_files_sampled184
oversized_source_files6

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — examples
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

250GitHub stars
27contributors
176commits, last 12 months
7days since last push
21releases
1bus factor
21open 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 ★ / 82 ⇿
0Stars
82Forks
20Releases

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.

0204060801008142025-072026-022026-09
Major 0Minor 18Patch 2

Each point covers 2 days.

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 · 2026-09-09 10:33 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
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
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
9Vulnerabilities1 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIanyio>=4.5pyproject.toml
PyPIcrowdstrike-falconpy>=1.6.4pyproject.toml
PyPImcp>=1.28.1,<2.0.0pyproject.toml
PyPIpython-dotenv>=1.1.1pyproject.toml
All dependencies 59

Full resolved dependency set from the GitHub dependency graph: 4 direct and 55 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIanyio4.9.0direct
PyPIcrowdstrike-falconpy1.6.4direct
PyPImcp1.29.0direct
PyPIpython-dotenv1.2.2direct
PyPIannotated-types0.7.0indirect
PyPIast-serialize0.5.0indirect
PyPIattrs25.3.0indirect
PyPIblack26.5.1indirect
PyPIcertifi2025.4.26indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.2indirect
PyPIclick8.4.1indirect
PyPIcolorama0.4.6indirect
PyPIcryptography50.0.0indirect
PyPIfalcon-mcp—indirect
PyPIfalcon-mcp0.19.0indirect
PyPIgoogle-adk2.5.0indirect
PyPIgoogle-cloud-aiplatform1.162.0indirect
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
PyPIpydantic2.13.4indirect
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
Dependency advisories 0

Installing pypi:falcon-mcp@0.19.0 pulls in 33 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 CrowdStrike/falcon-mcp. Read them side by side →

96mcp-use/mcp-useThe fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.Exceptional98n8n-io/n8nFair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.Exceptional98modelcontextprotocol/csharp-sdkThe official C# SDK for Model Context Protocol servers and clients. Maintained in collaboration with Microsoft.Exceptional96alpic-ai/skybridgeSkybridge is a full-stack TypeScript framework for MCP Apps and ChatGPT Apps. Type-safe. React-powered. Platform-agnostic.Exceptional95apify/apify-mcp-serverThe Apify MCP server enables your AI agents to extract data from social media, search engines, maps, e-commerce sites, or any other website using thousands of ready-made scrapers, crawlers, and automation tools available on the Apify Store.Exceptional94daangn/seed-designSEED Design SystemExceptional

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.