What can you do with this server?

The mcp-skylos server exposes Skylos static analysis capabilities to AI agents and coding assistants, enabling automated code quality, security, dead-code, and secrets analysis workflows. * analyze — Scan a codebase for dead code (unused functions, classes, imports, files) with configurable confidence threshold and folder exclusions. * security_scan — Detect vulnerabilities such as SQL injection, XSS, SSRF, and command injection. * quality_check — Check for quality regressions like excessive complexity, deep nesting, duplicate branches, and long functions. * secrets_scan — Detect exposed API keys, tokens, and high-entropy strings in the codebase. * remediate — Use an LLM to automatically suggest or apply fixes for security findings, with dry-run mode, severity filtering, and test command validation. * verify_dead_code — Use an LLM to verify dead code findings and reduce false positives. * provenance_scan — Scan for provenance and supply-chain issues, optionally scoped to a diff against a base branch. * generate_fix — Generate and optionally apply fixes (e.g., delete unused code) with a configurable safety threshold. * learn_triage — Record triage actions (accept/dismiss) on findings to improve future analysis. * get_triage_suggestions — Retrieve triage suggestions based on previously learned decisions for a project. * validate_code_change — Validate a unified diff for security regressions, dangerous patterns, secrets, and AI defense issues before merging. * get_security_context — Retrieve a security context summary for a codebase path to inform further analysis or LLM-assisted workflows.

Which integrations are available for this server?

Scans Docker Compose and other deployment configs for privileged access, host networking, missing sandboxing, and other edge-device security misconfigurations. Generates GitHub Actions PR gates with annotations and failure thresholds, and scans workflows for CI/CD misconfigurations. Scans GitLab CI configurations for dangerous triggers, unpinned actions/includes, broad tokens, and other supply-chain risks.

mcp-skylos by duriantaco

License: Apache 2.0 codecov PyPI - Python Version PyPI version VS Code Marketplace Astronomer Trust Discord

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What Is Skylos?

Skylos is an open-source static analysis CLI for Python, TypeScript, JavaScript, Java, Go, Kotlin, PHP, Rust, Dart, C#, Shell, and deployment config. It runs locally by default and can also be used as a CI/CD PR gate.

Use Skylos when you want one command to check a repo or pull request for:

dead code and unused files
security flaws and dangerous data flows
secrets and dependency CVEs
CI/CD and edge-device deployment misconfigurations
quality regressions such as complexity, duplicate branches, and deep nesting
common AI-generated code mistakes, including missing guards, fake helpers, invented package APIs, and impossible dependency versions
LLM app risks such as unsafe tool use and missing output validation

Related MCP server: open-code-review

Start In 60 Seconds

pip install skylos
skylos .

The default scan focuses on dead code. Add security, secrets, quality, and dependency checks with -a:

skylos . -a

Verify a changed file or range before an agent hands it to review:

skylos verify . --file src/app.py --range 40:75 --project-context

Create a project config with thresholds, ignores, template hooks, and vibe dictionary extensions:

skylos init

Create a starter local rule pack:

skylos rules init
skylos rules validate .skylos/rules/local.yml
skylos rules list --json
skylos rules list cross --json
skylos rules list --packs --json
skylos cache stats

Generate a GitHub Actions PR gate:

skylos cicd init
git add .github/workflows/skylos.yml
git commit -m "Add Skylos CI gate"
git push

Need more commands? Read the CLI Reference.

Common Workflows

Goal	Command	What You Get	More Detail
First dead-code scan	`skylos .`	Finds unused functions, classes, imports, files, and framework entrypoint mistakes	Dead code docs
Deterministic cleanup preview	`skylos clean . --dry-run --types import,function --confidence 80`	Shows safe import/function removals before writing; add `--apply` to edit files	Dead code docs
Security and quality audit	`skylos . -a`	Adds dangerous flow, secrets, dependency, config, and quality checks	Security docs
PR gate	`skylos cicd init`	Generates a GitHub Actions workflow with annotations and failure thresholds	CI/CD guide
Readable terminal report	`skylos . --format pretty`	Groups findings by file with severity badges, snippets, and copyable `file:line` locations	CLI output modes
Selectable terminal triage	`skylos . --tui`	Opens a keyboard-driven category list, finding list, and detail pane	CLI output modes
IDE/test-script output	`skylos --format concise src/test.py`	Prints only `file:line` findings and exits non-zero when findings exist	CLI Reference
In-loop AI-code verification	`skylos verify . --file src/app.py --range 40:75`	Returns narrow JSON for hallucinated helpers, unfinished code, stale references, disabled controls, and API/dependency hallucinations	AI features
Changed-lines review	`skylos . -a --diff origin/main`	Keeps findings focused on active work instead of legacy debt	Quality gate docs
Runtime-assisted dead-code check	`skylos . --trace`	Uses runtime traces to reduce dynamic-code false positives	Smart tracing
Local rule pack	`skylos rules init`	Scaffolds YAML rules for project-specific security and quality checks	Custom rules
Security agent quick scan	`skylos agent security-quick .`	One-shot LLM security audit; compatibility alias for `skylos agent scan . --security`	AI features
Security agent deep scan	`skylos agent security-deep .`	Three-stage security workflow with threat-model context, static threat traces, discovery/validation, and remediation handoff	AI features
AI-assisted review	`skylos agent scan .`	Static analysis plus optional LLM review and fix suggestions	AI features
Verification-backed remediation	`skylos agent scan . --fix`	Re-scans fixed security findings and records proof-test metadata for supported fixes	AI features
MCP agent verification	`verify_change` MCP tool	Lets Claude, Cursor, and other MCP clients verify an edited file/range with the same schema as `skylos verify`	MCP server
LLM app defense	`skylos defend .`	Finds missing AI app guardrails mapped to OWASP LLM risks	AI defense
Technical debt triage	`skylos debt .`	Ranks hotspots and debt trends	Technical debt

What Skylos Catches

Category	Examples	Why It Matters
Dead code	unused functions, classes, imports, package entrypoints, route handlers	reduces maintenance cost without breaking dynamic frameworks
Security flaws	SQL injection, XSS, SSRF, path traversal, command injection, unsafe deserialization	catches exploitable flows before code reaches main
Secrets	API keys, tokens, private credentials, high-entropy strings	prevents credentials from leaking through commits and PRs
CI/CD workflows	GitHub Actions and GitLab CI dangerous triggers, unpinned actions/includes, broad tokens, OIDC misuse, cache poisoning, mutable images	reduces CI/CD supply-chain risk before release jobs run
Edge deployment config	Docker Compose privileged device access, host networking, systemd root services, broad capabilities, missing sandboxing	catches repo-controlled settings that turn app bugs into device compromise
Quality regressions	complexity, deep nesting, duplicate branches, long functions, inconsistent returns	keeps AI-assisted refactors from adding brittle code
AI code mistakes	phantom security calls, missing decorators, unfinished stubs, disabled controls, real packages called with invented APIs, impossible npm/Go versions	catches common hallucinated or incomplete code paths before they reach review
LLM app risks	unsafe tool use, prompt injection exposure, missing output validation, missing rate limits	helps teams ship AI features with guardrails

See the full Rules Reference.

How Skylos Fits

Skylos is not a replacement for every specialized scanner. It is a local-first repo and PR checker that puts several common review checks behind one CLI.

Framework-aware dead code detection: FastAPI, Django, Flask, pytest, SQLAlchemy, Next.js, React, package entrypoints, and common plugin patterns.
PR-focused output: diff scanning, CI thresholds, GitHub annotations, and baselines for existing findings.
Local-first operation: core static analysis does not require cloud upload or LLM calls.
AI-assisted change review: checks for removed validation, auth, logging, CSRF, rate limiting, timeouts, real-package API hallucinations, and other guardrails in generated or edited code.
Agent-loop verification: skylos verify and MCP verify_change return versioned JSON for only AI-code trust findings, so coding agents can self-correct before a human sees the change.
Verification-backed remediation: security fixes are checked by re-running analysis, and supported findings can include targeted regression-test proof metadata.
Project-specific rules: add local YAML rules and extend prompt, credential, sensitive-file, and timeout dictionaries from config.
One command surface: dead code, security, secrets, dependency, quality, technical debt, agent review, and AI defense commands share the same CLI.

Install Options

# Core static analysis
pip install skylos

# LLM-powered agent workflows
pip install "skylos[llm]"

# All published optional extras
pip install "skylos[all]"

Container image:

docker pull ghcr.io/duriantaco/skylos:latest
docker run --rm -v "$PWD":/work -w /work ghcr.io/duriantaco/skylos:latest . --json --no-provenance

See Installation for source installs, container usage, and optional dependencies.

Configure Templates And Vibe Checks

Run skylos init to add these sections to pyproject.toml:

[tool.skylos.templates]
# security = ".skylos/templates/security.md"
# quality = ".skylos/templates/quality.md"
# security_audit = ".skylos/templates/security_audit.md"
# review = ".skylos/templates/review.md"

[tool.skylos.vibe]
extra_phantom_names = ["verify_enterprise_auth"]
extra_phantom_decorators = ["tenant_admin_required"]
extra_credential_names = ["tenant_signing_secret"]
extra_network_timeout_calls = ["vendor_sdk.fetch"]

[tool.skylos.dead_code]
entrypoints = []

[[tool.skylos.dead_code.entrypoints]]
type = "method"
name = ["create", "pre_hook", "post_hook"]
parent = { name = "Main", base_classes = ["Application"] }
path = "src/**"
reason = "project framework lifecycle hook"

[tool.skylos.contribution]
collect_local_signals = false
contribute_public_corpus = false
structural_signatures_only = true
include_source = false

Template files extend Skylos' built-in prompts; they do not replace the JSON-only output contract or untrusted-code safety rules. Vibe dictionary extensions let teams teach Skylos about local fake-auth helpers, project credential names, sensitive files, and network calls that must set timeouts. Dead-code entrypoints let teams mark proprietary framework classes, lifecycle methods, and decorator-registered functions as live using precise rules for type, name, path, decorators, base classes, and parent classes. Rules must include a symbol selector such as name, decorators, base_classes, or parent; path and module only narrow the match. Contribution signals are off by default; when enabled, Skylos records local structural accept/dismiss/learn events under .skylos/contribution/ without raw source.

By default Skylos discovers [tool.skylos] in pyproject.toml by walking up from the scan path. To use a dedicated TOML config, pass --config-file PATH or set SKYLOS_CONFIG_FILE; standalone files may use either [tool.skylos] or top-level [skylos]. Synced Skylos Cloud policy keeps its protected precedence over repository-controlled config.

Language Support

Language	Dead Code	Security	Quality	Notes
Python	Yes	Yes	Yes	strongest coverage; framework-aware static analysis and optional tracing
TypeScript / JavaScript	Yes	Yes	Yes	Tree-sitter parsing, package graph reachability, framework conventions
Java	Yes	Yes	Yes	Tree-sitter parsing and structured security-flow analysis
Go	Yes	Partial	Partial	dead-code and selected security benchmark coverage
PHP	Yes	Yes	Partial	PHP parser coverage plus taint-style security sinks and sources
Rust	Yes	Yes	Partial	Rust parser coverage plus security sink/source checks
Dart	Yes	Yes	Partial	Dart parser coverage plus selected security sinks and sources
C#	Yes	Yes	Partial	C# symbol coverage plus selected ASP.NET, process, SQL, HTTP, and file sinks
Shell	No	Yes	Partial	shell-script security checks for command injection, SSRF, and path traversal

See Rules Reference for rule families and scanner scope.

Config And Deployment Support

Surface	Files	Security Scope
GitHub Actions	`.github/workflows/.yml`, `.github/workflows/.yaml`, `action.yml`, `action.yaml`	dangerous triggers, token permissions, unpinned actions, template injection, secrets, OIDC, cache, and artifact policy
GitLab CI	`.gitlab-ci.yml`	mutable images, unpinned includes, literal secrets, untrusted eval, Docker-in-Docker, OIDC, cache, timeout, and runner-tag policy
Dockerfile	`Dockerfile`, `Dockerfile.`, `.dockerfile`	dangerous `RUN` commands, remote `ADD` without checksum, and literal build `ARG` / `ENV` secrets
Edge Docker Compose	`compose.yml`, `compose.yaml`, `docker-compose.yml`, `docker-compose.yaml`	privileged containers, broad host device/control mounts, GPU/device runtime, and host networking
Edge systemd	`*.service`	root edge services, mutable `ExecStart` paths, missing sandboxing, broad capabilities, and broad device access

Benchmark Snapshot

Skylos has checked-in regression benchmarks for dead code, security, quality, and agent review. These are strict regression gates, not broad proof that any tool is universally state of the art.

Suite	Current Skylos Result	Baseline
Dead code regression	16 cases, TP=36 FP=0 FN=0 TN=59, score 100.0	Ruff score 62.67; Vulture not installed in latest local rerun
Security regression	56 cases, TP=35 FP=0 FN=0 TN=23, score 100.0	Bandit score 47.14 on Python-applicable cases
Quality regression	13 cases, score 100.0	regression gate only
Agent review	25 cases, score 100.0	regression gate only
AI-code defect regression	curated verifier cases for hallucinated references, package APIs, and dependency versions	run `python scripts/ai_code_defect_benchmark.py`

Frozen golden-v0.2 highlights:

Frozen Suite	Skylos Result	Caveat
Dead code seeded dev	overall score 96.28; TS/JS/Go/Java score 100.0; Python score 93.33	Python residuals are label-review items
Security seeded dev	overall score 96.52; full recall with one Python `urljoin` false positive	label should be reviewed
OWASP Java security dev	TP=105 FP=0 FN=15 TN=120, score 94.37	request-wrapper, LDAP, XPath, and property weak-hash gaps remain
Quality seeded dev	TP=1 FP=0 FN=0 TN=1, score 100.0	one seeded case only

For methodology, commands, competitor rows, and caveats, see BENCHMARK.md.

Project Evidence

Skylos-assisted dead-code cleanup PRs have been merged in Black, NetworkX, Optuna, mitmproxy, pypdf, beets, and Flagsmith. These are accepted cleanup PRs, not project endorsements. See Real-World Results.

A local Astronomer scan on April 26, 2026 computed 420 stargazers and returned overall trust: A. StarGuard also reported low fake-star risk.

Integrations

Integration	Link	Purpose
GitHub Action	GitHub Action	PR gates, annotations, and CI enforcement
VS Code extension	VS Code extension	in-editor findings and AI-assisted fixes
MCP server	MCP setup	expose Skylos scans to AI agents and coding assistants
Docker image	Installation	run Skylos without a local Python install
Skylos Cloud	Cloud workflow	optional upload and dashboard workflows

Generate a GitHub Actions workflow from the CLI:

skylos cicd init --upload
skylos cicd init --upload --scan-path apps/api

The generated upload workflow uses GitHub OIDC, sends PR head commit/branch metadata, and supports monorepo subprojects through --scan-path.

Documentation Map

Need	Read This
Install options, source install, and Docker	Installation
First scan and core workflows	Quick Start
CLI commands, flags, and examples	CLI Reference
CLI output modes, pretty reports, and TUI controls	CLI Output Modes
CI setup, PR gates, annotations, and branch protection	CI/CD
Dead-code behavior and framework awareness	Dead Code Detection
Security scanning and taint analysis	Security Analysis
Rule ID prefixes and product terminology	Rule Dictionary
Agent scan, verification, remediation, and model setup	AI Features
AI defense checks and LLM guardrails	AI Defense
MCP server setup	MCP Server
Real-world merged cleanup PRs	Real-World Results
Baselines, filtering, suppressions, and whitelists	Configuration
Smart tracing	Smart Tracing
Rule families and language support	Rules Reference
Cloud uploads and dashboard flow	CLI to Dashboard
VS Code extension	VS Code Extension
Benchmarks and methodology	BENCHMARK.md
Security policy	SECURITY.md
Release process	RELEASE_WORKFLOW.md
Contribution priorities	ROADMAP.md
Contributing	CONTRIBUTING.md

Common Questions

Does Skylos replace Bandit, Semgrep, CodeQL, or Vulture?

No. Skylos can run alongside them. It focuses on framework-aware dead-code signal, PR gating, AI-era regression checks, and a combined workflow across dead code, security, secrets, and quality.

Does Skylos require an LLM?

No. Core static analysis runs locally without API keys. LLM features are optional through skylos[llm] and agent commands.

Can I use it only on changed code?

Yes. Use skylos . -a --diff origin/main locally or configure CI gates to focus on new findings.

How should I handle intentional dynamic code?

Use baselines, whitelists, inline suppressions, or runtime tracing. See the configuration docs and smart tracing docs.

Contributing And Support

Report security issues through SECURITY.md.
Open bugs and false-positive reports with minimal repros.
Check ROADMAP.md for useful contribution areas.
Read CONTRIBUTING.md before sending a pull request.
See QUALITY.md for project quality and gate expectations.
Join the Discord for community support.

License

Skylos is licensed under the Apache License 2.0.

Install Server

A

license - permissive license

D

quality

A

maintenance

How are these scores calculated?

Maintenance

–Maintainers

7hResponse time

4dRelease cycle

83Releases (12mo)

Commit activity

Issues opened vs closed

Resources

GitHub Repository

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