Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Open-source AI security agent: SAST, DAST, and policy-as-code over MCP.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"mythos-agent": {
"command": "npx",
"args": [
"-y",
"mythos-agent"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add mythos-agent -- npx -y mythos-agent프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"mythos-agent": {
"command": "npx",
"args": [
"-y",
"mythos-agent"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"mythos-agent": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mythos-agent"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 mythos-agent 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(4.0.1)은 7개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
English · 简体中文
mythos-agent AI code-review assistant for application security. Open-source. Reads your code, flags likely security issues, explains its reasoning, suggests fixes.
mythos-agent.com
Quick Start • How It Works • Commands • Hunt Mode • Variant Analysis • Integrations • Contributing • Vision • Roadmap
mythos-agent reviews your code the way a reviewer on a security-focused team would. It walks through likely issue patterns, checks for variants of known CVEs, ranks findings by confidence, and suggests fixes you can accept or reject. See VISION.md for the full framing.
For new contributors: the active 6-month working plan is in the pinned issue `[Roadmap] mythos-agent H1 2026 Goals`. Look for 🙋 markers to spot items where help is wanted. New here? See CONTRIBUTING.md for
good-first-issueguidance.
For security teams and EU CRA-compliant downstream manufacturers: see SECURITY.md for our vulnerability disclosure SLAs, docs/security/cra-stance.md for our EU CRA role declaration, docs/security/threat-model.md for our public threat model, and RELEASES.md for our versioning, LTS, and EOL policy. OpenSSF Best Practices Badge (Passing) submission targeted June 2026; releases are signed via Sigstore and ship with CycloneDX SBOMs for downstream Manufacturer compliance.
npx mythos-agent hunt
🔐 mythos-agent hunt — AI Code-Review Assistant
✔ Phase 1: Reconnaissance — 12 entry points, express, typescript, postgresql ✔ Phase 2: Hypothesis — 8 security hypotheses generated ✔ Phase 3: Analysis — 15 findings (semgrep, gitleaks, trivy, built-in), 22 false positives dismissed ✔ Phase 4: Reproduction — 2 finding chains, 3 reproductions
🧪 Security Hypotheses
[HIGH] HYPO-001 — Race condition: concurrent payment requests could double-charge src/payments.ts:45 (race-condition) [HIGH] HYPO-002 — Auth bypass: JWT token not validated after password change src/auth.ts:78 (auth-bypass)
📊 Confidence Summary
3 confirmed | 8 likely | 4 possible | 22 dismissed
⛓️ FINDING CHAINS
CRITICAL SQL Injection → Auth Bypass → Data Exfiltration ├── src/api/search.ts:45 — unsanitized input in SQL query ├── src/middleware/auth.ts:88 — JWT verification skippable └── src/api/export.ts:23 — bulk export has no ACL
🧪 Reproductions
SPX-0001 — SQL injection in search endpoint See repro steps in docs/reproductions/SPX-0001.md
Trust Score: 2.3/10 — critical issues found
# Install
npm install -g mythos-agent
mythos-agent scan
mythos-agent init mythos-agent hunt
mythos-agent variants CVE-2021-44228
mythos-agent ask "are there any auth bypasses?"
mythos-agent tools
mythos-agent combines three things no other open-source tool does together:
Instead of matching known patterns, the AI reasons about what COULD go wrong, generating hypotheses like "this transaction doesn't lock the row, potential race condition" or "this auth check uses string comparison, potential timing attack."
Given a known CVE, mythos-agent finds structurally similar but syntactically different code in your codebase. Same root cause, different location. This is how Google's Big Sleep found 20 real zero-days.
Every finding goes through a confidence pipeline:
Only findings that survive multiple stages are reported as "confirmed."
| Command | Description |
|---|---|
hunt [path] | Full autonomous multi-agent scan (Recon → Hypothesize → Analyze → Exploit) |
scan [path] | Standard scan (patterns + secrets + deps + IaC + AI) |
variants [cve-id] | Find variants of known CVEs in your codebase |
fix [path] | AI-generated patches with --apply |
ask [question] | Natural language security queries |
taint [path] | AI data flow / taint analysis |
watch | Continuous monitoring that scans on file save |
dashboard | Local web UI with charts and findings table |
report [path] | Export as terminal / JSON / HTML / SARIF |
policy | Policy-as-code with SOC2/HIPAA/PCI/OWASP compliance |
rules | Community rule pack registry (search/install/publish) |
tools | Check which external security tools are installed |
init | Setup wizard (Anthropic, OpenAI, Ollama, LM Studio) |
mythos-agent hunt runs the full multi-agent pipeline:
┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Recon │ → │ Hypothesis │ → │ Analyze │ → │ Exploit │ │ Agent │ │ Agent │ │ Agent │ │ Agent │ ├──────────────┤ ├──────────────┤ ├──────────────┤ ├──────────────┤ │ Map entry │ │ Reason about │ │ All scanners │ │ Chain vulns │ │ points, auth │ │ what could │ │ + external │ │ + generate │ │ boundaries, │ │ go wrong per │ │ tools + AI │ │ PoC exploits │ │ data stores │ │ function │ │ verification │ │ │ └──────────────┘ └──────────────┘ └──────────────┘ └──────────────┘
Find code in your project that has the same root cause as known CVEs:
# Search for Log4Shell-like patterns
mythos-agent variants CVE-2021-44228
mythos-agent variants --auto
The variant analyzer extracts the root cause pattern from the CVE (not the surface syntax) and searches your codebase for structurally similar code.
The Default scanners run on every mythos-agent scan. Experimental scanners are implemented + unit-tested classes that ship in the tarball but are not yet reachable from any CLI, HTTP, MCP, or agent entry point. They are tracked by KNOWN_EXPERIMENTAL in the wiring-invariant test.
| Category | What it finds | Rules | Status |
|---|---|---|---|
| Code patterns | SQLi, XSS, command injection, eval, SSRF, etc. | 25+ | Default |
| Framework rules | React, Next.js, Express, Django, Flask, Spring, Go | 27 | Default |
| Secrets | AWS, GitHub, Stripe, API keys, DB URLs, private keys + entropy | 22 | Default |
| Dependencies (SCA) | Known CVEs via OSV API (10 lockfile formats) | OSV | Default |
| IaC | Docker, Terraform, Kubernetes misconfigurations | 13 | Default |
| AI/LLM Security | Prompt injection, unsafe eval of AI output, cost attacks | 13 | Default |
| API Security | OWASP API Top 10: BOLA, mass assignment, broken auth | 12 | Default |
| Cloud Misconfig | AWS/Azure/GCP: public storage, wildcard IAM, open firewalls | 14 | Default |
| Security Headers | CSP, HSTS, X-Frame-Options, Referrer-Policy | 8 | Default |
| JWT | Algorithm, expiry, storage, revocation, audience | 9 | Default |
| Session | Fixation, expiry, cookie flags, localStorage tokens | 7 | Default |
| Business Logic | Negative amounts, coupon reuse, inventory races, role escalation | 6 | Default |
| Crypto Audit | Weak hashes, ECB mode, hardcoded keys, deprecated TLS | 11 | Default |
| Privacy/GDPR | PII handling, consent, data retention (GDPR article mapping) | 9 | Default |
| Race Conditions | TOCTOU, non-atomic ops, double-spend, missing transactions | 7 | Default |
| ReDoS | Catastrophic backtracking in regex (nested quantifiers, overlapping alternatives) | — | Default |
| Supply Chain | Typosquatting, dependency confusion, dangerous install scripts | 12 | Experimental |
| Zero Trust | Service trust, mTLS, network segmentation, IP-based auth | 8 | Experimental |
| GraphQL | Introspection, depth limit, field auth, batching | 8 | Experimental |
| WebSocket | Auth, origin check, message validation, broadcast XSS | 7 | Experimental |
| CORS | Origin reflection, credentials handling, substring bypass | 7 | Experimental |
| OAuth/OIDC | Missing state, no PKCE, implicit flow, client secret exposure | 7 | Experimental |
| SSTI | Jinja2, EJS, Handlebars, Pug, Nunjucks, Twig, Go templates | 7 | Experimental |
Additional experimental scanners (21 more, not yet wired into default scan)
SQL injection deep, XSS deep, NoSQL, command injection, deserialization, path traversal, open redirect, XXE, input validation, clickjacking, DNS rebinding, subdomain enumeration, dep confusion, environment variables, logging, error handling, cache, email, upload, memory safety, permissions.
Each exists as a class under src/scanner/ and has unit tests in src/scanner/__tests__/coverage-scanners.test.ts / new-scanners.test.ts, but is not invoked by any CLI command, HTTP API route, MCP handler, or agent pipeline. See KNOWN_EXPERIMENTAL in the wiring-invariant test for each scanner's deferral reason. Wiring one up follows the pattern of the HeadersScanner / JwtScanner / SessionScanner / BusinessLogicScanner commits on main.
Beyond the scanners above, mythos-agent ships complementary analyses (not counted in the scanner totals): call-graph + taint engine, DAST smart fuzzer, AI hypothesis agent, variant analysis, and git-history mining.
External tool integrations: Semgrep (30+ languages), Gitleaks (100+ patterns), Trivy (SCA + containers), Checkov (1000+ IaC policies), Nuclei (9000+ DAST templates)
| Platform | What |
|---|---|
| VS Code | Extension with inline diagnostics + one-click AI fix |
| GitHub Action | Scan on push/PR + SARIF upload to Code Scanning |
| PR Review Bot | Inline comments on vulnerable lines in pull requests |
| Dashboard | Local web U
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요