io.github.mythos-agent/mythos-agent MCP Server
io.github.mythos-agent/mythos-agent
AI code-review assistant that hunts security issues via hypothesis-driven scanning, variant analysis, and multi-stage verification.
What is the io.github.mythos-agent/mythos-agent MCP server?
mythos-agent is an open-source AI security agent that reviews code for application security vulnerabilities using SAST, DAST, and policy-as-code over MCP. It combines hypothesis-driven scanning, variant analysis of known CVEs, and multi-stage verification to identify and explain security issues with suggested fixes.
mythos-agent automates security code review by reasoning about what could go wrong in your codebase, finding variants of known CVEs, and verifying findings through pattern scanning, AI analysis, and dynamic testing. It integrates 15+ wired scanners covering SQL injection, XSS, secrets, dependencies, IaC, JWT, session management, business logic, and more—plus external tools like Semgrep, Gitleaks, Trivy, and Nuclei. Use it to scan code, hunt for security hypotheses, analyze CVE variants, generate PoCs, and enforce compliance policies.
How to install io.github.mythos-agent/mythos-agent
Copy-paste configuration for popular MCP clients.
Tools & capabilities
Tools this server exposes to the agent.
hunt— Full autonomous multi-agent scan combining reconnaissance, hypothesis generation, analysis, and exploitation stagesscan— Standard security scan with pattern matching, secrets detection, dependency checking, IaC analysis, and AI verificationvariants— Find structurally similar code in your codebase that shares the root cause of known CVEsask— Natural language security queries to investigate specific security concernsfix— AI-generated security patches with optional automatic applicationtaint— AI-powered data flow and taint analysiswatch— Continuous monitoring that scans code on file savedashboard— Local web UI with findings visualization, charts, and results tablereport— Export findings in terminal, JSON, HTML, or SARIF formatpolicy— Policy-as-code engine for SOC2, HIPAA, PCI-DSS, and OWASP compliance mappingrules— Community rule pack registry for searching, installing, and publishing custom rulestools— Check which external security tools are installed and available
Use cases
- Scan codebases for SQL injection, XSS, command injection, SSRF, and other OWASP Top 10 vulnerabilities
- Find variants of known CVEs (e.g., Log4Shell) in your code that share the same root cause but different syntax
- Generate proof-of-concept exploits and vulnerability chains to validate security findings
- Enforce compliance policies (SOC2, HIPAA, PCI-DSS) and security standards across your codebase
- Integrate security scanning into CI/CD pipelines via GitHub Actions and get inline PR review comments
io.github.mythos-agent/mythos-agent MCP server FAQ
mythos-agent is an open-source AI code-review assistant that hunts security vulnerabilities using hypothesis-driven scanning, variant analysis of known CVEs, and multi-stage verification. It combines pattern scanning, AI reasoning, and dynamic testing to identify and explain security issues with suggested fixes.
Yes, mythos-agent is open-source under the MIT license. Pattern scanning, secrets detection, dependency checks, and IaC analysis work without any API key. AI-powered features (hypothesis generation, variant analysis, PoC generation) require an API key from Anthropic, OpenAI, or compatible providers.
mythos-agent is available as an npm package (`npm install -g mythos-agent`) and exposes its capabilities via MCP (Model Context Protocol). You can configure it as an MCP server in Cursor or Claude to enable AI agents to run security scans, ask security questions, and generate fixes directly within your editor.
Pattern scanning, secrets detection, dependency analysis, and IaC checks require no authentication. AI-powered features (hypothesis generation, variant analysis, PoC generation, auto-fix) require an API key from Anthropic Claude, OpenAI, Ollama, LM Studio, or any OpenAI-compatible provider.
mythos-agent ships with 15 wired scanners covering SQL injection, XSS, secrets, dependencies (SCA), IaC, JWT, session management, business logic, crypto, privacy/GDPR, race conditions, and more. It integrates external tools like Semgrep, Gitleaks, Trivy, Checkov, and Nuclei, plus AI-powered analyses: call-graph, taint engine, DAST fuzzing, and variant analysis.
Yes. mythos-agent can generate AI-powered security patches via the `fix` command with an optional `--apply` flag to automatically apply patches. It also generates proof-of-concept exploits and vulnerability chains to validate findings.
README (reference)
Source of truth, from the repository.
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 forgood-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
Quick Start
# Install
npm install -g mythos-agent
# Quick scan (no API key needed)
mythos-agent scan
# Full autonomous hunt (needs API key)
mythos-agent init
mythos-agent hunt
# Find variants of known CVEs
mythos-agent variants CVE-2021-44228
# Ask security questions
mythos-agent ask "are there any auth bypasses?"
# Check available tools
mythos-agent tools
How It Works
mythos-agent combines three things no other open-source tool does together:
1. Hypothesis-Driven Scanning
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."
2. Variant Analysis (Big Sleep technique)
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.
3. Multi-Stage Verification
Every finding goes through a confidence pipeline:
- Pattern scan → candidate
- AI hypothesis → theoretical risk confirmed
- Smart fuzzer → dynamically tested
- PoC generator → concrete exploit proves it's real
Only findings that survive multiple stages are reported as "confirmed."
Commands
| 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) |
Hunt Mode
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 │ │ │
└──────────────┘ └──────────────┘ └──────────────┘ └──────────────┘
Variant Analysis
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
# Auto-detect and scan for variants
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.
Scanners (15 wired + 28 experimental, 329+ rules)
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 |
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)
Integrations
| 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 UI at mythos-agent dashboard |
| SARIF | GitHub Code Scanning, VS Code, any SARIF tool |
| Policy Engine | SOC2, HIPAA, PCI-DSS, OWASP compliance mapping |
AI Providers
| Tier | Providers | Status |
|---|---|---|
| 1 — Primary | Anthropic (Claude Sonnet / Opus / Haiku) | Fully tested. Published catch-rate numbers in docs/benchmarks/external-scores.md are produced with this tier. |
| 2 — Compatible (proxy today, native in stage 2) | Anything OpenAI-compatible — OpenAI, Qwen via DashScope/OpenRouter, Gemini, Mistral, vLLM, Ollama, LM Studio, Bedrock, etc. | Today: route through any Anthropic-compatible proxy (LiteLLM, OpenRouter, Vercel AI Gateway, Bedrock) by setting baseURL in .mythos.yml or ANTHROPIC_BASE_URL env. Native OpenAI SDK support lands in stage 2. |
| 3 — Local / community | Local Ollama / LM Studio / vLLM | Same code path as Tier 2; called out separately because privacy and cost-of-zero are the use case. Best-effort; agentic tool-use quality depends on local model size. |
Pattern scanning, secrets, deps, and IaC work without any API key.
See docs/multi-model.md for the full tier-system policy + the staged rollout (this README is the summary; that doc is the canonical reference).
Comparison
| Feature | mythos-agent | Semgrep | Snyk | CodeQL | Nuclei |
|---|---|---|---|---|---|
| Pattern scanning | Yes | Best | Yes | Yes | Templates |
| Hypothesis scanning | Yes | No | No | No | No |
| Variant analysis | Yes | No | No | Partial | No |
| AI-guided fuzzing | Yes | No | No | No | Templates |
| PoC generation | Yes | No | No | No | No |
| AI deep analysis | Yes | No | Limited | No | No |
| Vuln chaining | Yes | No | No | No | No |
| AI auto-fix | Yes | No | Fix PRs | No | No |
| NL queries | Yes | No | No | No | No |
| Secrets | Yes | Yes | Yes | No | No |
| SCA | Yes | No | Best | No | No |
| IaC | Yes | No | Yes | No | Templates |
| DAST | Yes | No | No | No | Best |
| Open source | Yes | Partial | No | Yes | Yes |
This feature table is a capability comparison, not an accuracy claim. For reproducible, third-party-runnable accuracy numbers vs Semgrep CE / Snyk Code / CodeQL on OWASP Benchmark, CyberSecEval 3, Vul4J, and our CVE replay harness, see docs/benchmarks/external-scores.md.
Contributing
See CONTRIBUTING.md for details.
git clone https://github.com/mythos-agent/mythos-agent.git
cd mythos-agent && npm install && npm run build && npm test
Architecture
src/
agents/ Multi-agent orchestrator + Recon/Hypothesis/Analyzer/Exploit agents
analysis/ Code parser, call graph, taint engine, variant analyzer, service mapper
agent/ AI integration, prompts, tools, fix validator
cli/ 44 CLI commands
dast/ Smart fuzzer, PoC generator, payload library
policy/ Policy engine + compliance mapping
report/ Terminal, JSON, HTML, SARIF, dashboard
rules/ Built-in + custom YAML + community registry
scanner/ Pattern, secrets, deps, IaC, diff scanners
store/ Results persistence + incremental cache
tools/ External tool wrappers (Semgrep, Trivy, etc.)
vscode-extension/ VS Code extension
action/ GitHub Actions
bot/ PR Review Bot
License
MIT
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