Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-12 19:20 UTC

sjkim1127 / Reversecore_MCP

A security-first MCP server that empowers AI agents to perform automated reverse engineering, malware analysis, forensics, vulnerability research, and SAST — powered by Radare2, YARA, LIEF, Capstone, and more.

PythonMIT★ 201 stars⑂ 20 forkssince Nov 2025View on GitHub ↗
KindCommand-line toolMCP serverNetwork serviceLibraryhow this is determined
#mcp-server#reverse-engineering#mcp#ghidra#radare2#security#mcp-security#sast

sjkim1127/Reversecore_MCP holds a health index of 84 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Community & Adoption (51/100). It was last updated today. A single contributor accounts for most of its recent work.

84
overall / 100
Excellent

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.

84
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 71 is calibrated to 84 on the published index scale (record calibration 2026-08-02).

Ownership

Sung Joo KimPersonal account
58 followers13 public repossince Sep 2024

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
PyPIreversecore-mcp3.0.3-229 days agomcpmodel-context-protocolreverse-engineeringmalware-analysisdigital-forensicsvulnerability-researchradare2yara

Metrics by category

Vitality

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

87Excellent · 21% of overall

Development activity

85Excellent
How it's scored
36/36Push recency — last push 0 days ago
20.8/36Commit cadence — 30/52 weeks with commits
18/18Commit volume — 861 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year861
human_commit_share0.94
days_since_last_push0
active_weeks_last_year30

Release discipline

90Excellent
How it's scored
27/27Ships releases — 46 releases published
36/36Release recency — latest release 29 days ago
27/27Release cadence — a release every ~26.2 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count46
latest_release_tagv3.0.3
releases_from_tagsno
days_since_latest_release29
mean_days_between_releases26.2

Community & Adoption

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

51Moderate · 17% of overall

Popularity & adoption

52Moderate
How it's scored
37.3/60Stars — 201 stars
10.7/25Forks — 20 forks
3.9/15Watchers — 6 watchers
Inputs used
forks20
stars201
watchers6
growth_stateorganic
growth_factor_pct100

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_badges11
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesapi.securityscorecards.dev, github.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

52Moderate · 23% of overall

Maintainer resilience (bus factor)

13Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.1/22.5Commit distribution — top contributor authored 100% of commits
4.1/13.5Contributor breadth — 3 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.997

Issue & PR responsiveness

76Good
How it's scored
42/42Issue resolution — 100% of issues closed
24/30PR acceptance — 128/160 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_prs128
open_issues0
closed_issues4
prs_merged_7d0
prs_decided_7d0
prs_merged_30d3
prs_decided_30d3
issue_closed_ratio1
closed_unmerged_prs32
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

44Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
12.7/25Owner reach — 58 followers of sjkim1127
12.3/25Track record — 13 public repos, account ~1 yr old
Inputs used
followers58
owner_typeUser
is_verified—
owner_loginsjkim1127
public_repos13
account_age_days715
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

92Excellent
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 29 days ago
12/20Version history — 2 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesreversecore-mcp
ecosystemspypi
any_deprecatedno
min_days_since_publish29

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 8 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 — 1 out of 1 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://github.com/sjkim1127/Reversecore_MCP#readme
10/10Repository description
10/10Topics — 8 topics
10/10Wiki
Inputs used
topicsmcp-server, reverse-engineering, mcp, ghidra, radare2, security, mcp-security, sast
has_wikiyes
homepage—
docs_sitehttps://github.com/sjkim1127/Reversecore_MCP#readme
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

69Good · 16% of overall

Security posture

61Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 1 out of 1 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
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
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 2 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool detected
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 42 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.1
Excluded from scoring (no data or not applicable): Branch-Protection. 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_packages139
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:reversecore-mcp@3.0.3 runtime dependency closure — what installing the published package pulls in — 139 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.

75Good · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — AGENTS.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://lief-project.github.io/llms.txt)
40/40Legible commit history — 93 of 94 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://lief-project.github.io/llms.txt
legible_history_share0.989
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes10,827

Verify loop (build / test / typecheck)

59Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — reversecore_mcp/py.typed
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
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_configyes
typecheck_configsreversecore_mcp/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (reversecore_mcp/py.typed)
54.4/55Manageable file sizes — 4/394 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes130,593
source_files_sampled394
oversized_source_files4

Machine-readable interfaces

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

Key facts

201GitHub stars
3contributors
861commits, last 12 months
0days since last push
46releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Star history carried forward from 2026-07-16: GitHub restricted the stargazers API to repository admins, so it can no longer be collected. The repository has 201 stars today.
  • pypi download statistics for 'reversecore-mcp' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 181 ★ / 20 ⇿
181Stars
20Forks
37Releases

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.

Star history is shown as collected on 2026-07-16. GitHub restricted the stargazers API to repository administrators in July 2026, so this series can no longer be extended; the current star total above remains live.

0408012016020018120442025-112026-042026-08
Major 2Minor 4Patch 31
OpenSSF Scorecard 6.1 / 10
6.1aggregate

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 · 2026-09-12 19:19 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests1 out of 1 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
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool detected
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities42 existing vulnerabilities detected
Direct dependencies 27
RegistryPackageVersion constraintManifest
PyPImcp>=1.27.0pyproject.toml
PyPIfastmcp==3.4.4pyproject.toml
PyPIfastapi>=0.100.0pyproject.toml
PyPIuvicorn>=0.30.0pyproject.toml
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PyPIpyxdia<=0.1.0pyproject.toml
PyPIpwntools>=4.12.0pyproject.toml
PyPIROPgadget>=7.3pyproject.toml
All dependencies 315

Full resolved dependency set from the GitHub dependency graph: 53 direct and 262 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIpython-bidi0.6.10indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-flirt0.9.10indirect
PyPIpython-magic—indirect
PyPIpython-magic0.4.27indirect
PyPIpython-magic-bin—indirect
PyPIpytokens0.4.1indirect
PyPIpyvex9.2.213indirect
PyPIpyyaml6.0.3indirect
PyPIpyyaml-env-tag1.1indirect
PyPIquestionary2.1.1indirect
PyPIr2pipe—indirect
PyPIr2pipe1.9.8indirect
PyPIreferencing0.37.0indirect
PyPIreportlab4.5.1indirect
PyPIrequests—indirect
PyPIrequests2.34.2indirect
PyPIrich—indirect
PyPIrich15.0.0indirect
PyPIrich-click1.9.8indirect
PyPIrich-rst2.1.0indirect
PyPIrpds-py0.30.0indirect
PyPIrpyc6.0.2indirect
PyPIruamel-yaml0.19.1indirect
PyPIruff—indirect
PyPIruff0.15.21indirect
PyPIscapy—indirect
PyPIscapy2.7.0indirect
PyPIsecretstorage3.5.0indirect
PyPIsemantic-version2.10.0indirect
PyPIsetuptools—indirect
PyPIsetuptools83.0.0indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIslowapi—indirect
PyPIslowapi0.1.10indirect
PyPIsmmap5.0.3indirect
PyPIsortedcontainers2.4.0indirect
PyPIsse-starlette3.4.5indirect
PyPIstarlette1.3.1indirect
PyPIsvglib2.0.2indirect
PyPIsympy1.14.0indirect
PyPItenacity9.1.4indirect
PyPItibs0.5.7indirect
PyPItinycss21.5.1indirect
PyPItyper—indirect
PyPItyper0.26.8indirect
PyPItypes-requests—indirect
PyPItypes-requests2.33.0.20260518indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzlocal5.4.3indirect
PyPIuefi-firmware1.16indirect
PyPIuncalled-for0.3.2indirect
PyPIunicorn2.1.2indirect
PyPIunix-ar0.2.1indirect
PyPIuritools6.1.2indirect
PyPIurllib32.7.0indirect
PyPIviv-utils0.8.1indirect
PyPIvivisect1.3.2indirect
PyPIvolatility3—indirect
PyPIvolatility32.28.0indirect
PyPIwatchdog6.0.0indirect
PyPIwatchfiles1.2.0indirect
PyPIwcwidth0.8.2indirect
PyPIwebencodings0.5.1indirect
PyPIwebsockets16.1indirect
PyPIwheel0.47.0indirect
PyPIwrapt2.2.2indirect
PyPIxmltodict1.0.4indirect
PyPIyara-python—indirect
PyPIyara-python4.5.4indirect
PyPIz3-solver4.13.0.0indirect
PyPIzipp4.1.0indirect
PyPIzstandard0.25.0indirect
Dependency advisories 0

Installing pypi:reversecore-mcp@3.0.3 pulls in 139 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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100stacklok/toolhiveToolHive is an enterprise-grade platform for running and managing Model Context Protocol (MCP) servers.Exceptional96stacklok/toolhive-registry-serverDiscover, govern and control access to MCP servers and agent skills across your organizationExceptional99IBM/mcp-context-forgeAn AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent & Tool calling, and supports plugins.Exceptional96PrefectHQ/fastmcp🚀 The fast, Pythonic way to build MCP servers and clients.Exceptional96mcp-use/mcp-useThe fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.Exceptional95dbt-labs/dbt-mcpA MCP (Model Context Protocol) server for interacting with dbt.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.