agentwise

The fast, offline security scanner for AI agent configurations.

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Think npm audit, but for MCP servers and AI agents.

$ agentwise scan .

  ╔══════════════════════════════════════════════════════════════╗
  ║  agentwise v0.1.0                                          ║
  ║  MCP Security Scanner                                      ║
  ╚══════════════════════════════════════════════════════════════╝

  ● Scanned 3 configs (12 servers) in 4ms

  ┌──────────────────────────────────────────────────────────────┐
  │  ■ 3 critical  ■ 5 high  ■ 7 medium  ■ 0 low               │
  └──────────────────────────────────────────────────────────────┘

  ✖ CRITICAL  .mcp.json → filesystem  AW-002
    Filesystem server with dangerous root access
    Fix: Add "allowedDirectories" to restrict to project directories

  ✖ CRITICAL  .mcp.json → quickbooks  AW-001
    No authentication on remote MCP server
    Fix: Add authentication via env vars (AUTH_TOKEN, API_KEY, etc.)

  ▲ HIGH      .mcp.json → filesystem  AW-006
    CVE-2025-53110: Path traversal in server-filesystem <0.6.3
    Fix: Upgrade to >=0.6.3

  ╔══════════════════════════════════════════════════════════════╗
  ║  Score: 12/100  ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  Grade: F   ║
  ╚══════════════════════════════════════════════════════════════╝

How it works

Why agentwise?

30+ CVEs against MCP servers in the last 60 days. 36% of MCP servers ship with zero authentication. Your AI agent setup is probably vulnerable.

Every existing scanner is Python, JavaScript, or TypeScript. They need pip install or npm install, pull dozens of dependencies, and some require LLM API calls that cost money per scan.

	agentwise	Snyk agent-scan	Cisco mcp-scanner	mcp-shield
Language	Rust	Python	Python	TypeScript
Install	Single binary	pip / uvx	pip	npm
Speed class	Milliseconds	Seconds	Seconds	Seconds
Offline	Yes	No	No	Yes
EPSS scoring	Yes	No	No	No
Supply chain	Yes	No	No	No
deps.dev	Yes	No	No	No

Performance (measured)

Measured on macOS arm64, release build, using hyperfine.

agentwise scan latency

Command	Mean time
agentwise scan testdata/vulnerable-mcp.json (5 servers)	3.2 ms
agentwise scan research/configs/ (109 servers)	3.9 ms

Quick head-to-head (same vulnerable fixture)

Tool	Mean runtime
agentwise	3.1 ms
Cisco mcp-scanner (--analyzers yara)	2.68 s
mcp-shield (default run)	60.62 s

Notes:

• These are default CLI runs on the same fixture (testdata/vulnerable-mcp.json).
• Some tools attempt live server connections by design, which increases runtime.
• Reproduce locally with the benchmark commands in research/benchmarks.md.

Real-world findings snapshot

From a scan of 109 MCP server entries collected from public GitHub configs + official docs:

• 130 total findings (13 high, 117 medium)
• 100% missing tool allowlists (AW-007)
• 8.26% had unrestricted filesystem access (AW-002)
• 1.83% exposed hardcoded secrets (AW-004)
• Insecure cleartext transport and wildcard bind exposure (http://, ws://, 0.0.0.0, [::]) still show up in public configs (AW-005)

Full methodology, source attribution, and raw output are in research/FINDINGS.md and research/scan-results.json.

Trust signals

• 4.0 MB release binary
• 255/255 tests passing
• 0 clippy warnings with -D warnings
• 0 known Rust dependency vulnerabilities (cargo audit)

Install

From crates.io (coming soon)

agentwise is not published on crates.io yet.

Install with Cargo today

cargo install --git https://github.com/brandonwise/agentwise agentwise

Build from source now

git clone https://github.com/brandonwise/agentwise
cd agentwise
cargo build --release
./target/release/agentwise --version

Pre-built binary

curl -sSf https://raw.githubusercontent.com/brandonwise/agentwise/main/install.sh | sh

Homebrew

brew tap brandonwise/tap
brew install agentwise

Scan workflow

Quick Start

# Scan current directory (auto-detects MCP configs)
agentwise scan .

# Scan a specific config file
agentwise scan ~/.mcp.json

# Scan a Codex MCP config
agentwise scan ~/.codex/config.toml

# Live mode: query OSV + EPSS for real-time CVE data
agentwise scan . --live

# Supply chain analysis (npm registry + deps.dev)
agentwise scan . --supply-chain

# Fail CI on high+ severity findings
agentwise scan . --fail-on high

Supported Configs

agentwise auto-detects and scans:

• .mcp.json — Claude Code project-level configs
• claude_desktop_config.json — Claude Desktop
• .cursor/mcp.json — Cursor editor
• ~/.codex/config.toml and .codex/config.toml — Codex CLI + IDE
• mcp.json — Generic MCP configs
• Any JSON file with mcpServers or context_servers passed as argument
• Any Codex config.toml with [mcp_servers.<name>] tables passed as argument

Threat coverage

Detection Rules

12 built-in rules, covering misconfigurations, known CVEs, and supply chain risks:

ID	Rule	Severity
AW-001	No authentication on remote server	Critical
AW-002	Overpermissioned filesystem access	Critical
AW-003	Unrestricted shell/exec access	Critical
AW-004	Secrets in plaintext config	High
AW-005	Insecure transport or wildcard bind exposure (http://, ws://, 0.0.0.0, [::])	High
AW-006	Known CVE match (embedded + OSV)	Critical/High
AW-007	Missing tool allowlist	Medium
AW-008	Write-capable tools without opt-in	Medium
AW-009	Unrestricted network/fetch tools	Medium
AW-010	Prompt injection surface	Medium
AW-011	Supply chain risk signals	High/Medium
AW-012	Deep dependency chain (deps.dev)	High/Medium

Live Mode

The --live flag queries OSV.dev for real-time vulnerability data and FIRST EPSS for exploitation probability scores. This tells you not just what is vulnerable, but how likely it is to be exploited in the wild.

$ agentwise scan . --live

  ...

  ▲ HIGH      .mcp.json → filesystem  AW-006 [LIVE]
    CVE-2025-53110: Path traversal in server-filesystem <0.6.3
    EPSS: 72% exploitation probability (95th percentile)
    Fix: Upgrade to >=0.6.3

  ● Live CVE check: queried OSV for 8 packages (2 new vulnerabilities found)

  ...

EPSS scores above 50% are flagged as actively exploited in the wild. The --offline flag disables all network queries and uses only the embedded database.

Supply Chain Analysis

The --supply-chain flag analyzes each MCP server's npm package for supply chain risk signals: single-maintainer packages, typosquatting, install scripts, low download counts, and dependency graph depth via deps.dev.

$ agentwise scan . --supply-chain

  ...

  ▲ HIGH      .mcp.json → sketchy-mcp  AW-011 [SUPPLY-CHAIN]
    Supply chain risk: HIGH for sketchy-mcp
    ├ Single maintainer 'anon42' (account takeover risk)
    ├ Has postinstall script
    └ 43 weekly downloads
    Fix: Review package provenance and consider official @modelcontextprotocol packages

  ● MEDIUM    .mcp.json → some-tool  AW-012 [DEPS.DEV]
    Deep dependency chain: 247 transitive deps
    ├ 247 transitive dependencies (high risk)
    └ 2 transitive deps have known advisories
    Fix: Review transitive dependencies and update packages with advisories

  ...

CI/CD Integration

GitHub Actions (manual, available now)

- name: Install agentwise
  run: curl -sSf https://raw.githubusercontent.com/brandonwise/agentwise/main/install.sh | sh

- name: Scan MCP configs
  run: agentwise scan . --fail-on high --format sarif > agentwise.sarif

- uses: github/codeql-action/upload-sarif@v3
  with:
    sarif_file: agentwise.sarif

The --fail-on flag exits with code 1 when findings at or above the specified severity are found, gating your pipeline.

Output Formats

agentwise scan .                                        # Colorized terminal output (default)
agentwise scan . --format json                          # JSON for scripting and pipelines
agentwise scan . --format sarif                         # SARIF for GitHub Code Scanning
agentwise scan . --format html --output report.html     # Dark-themed HTML report
agentwise scan . --format markdown                      # Markdown for PRs/Notion/Confluence
agentwise badge --format svg --output badge.svg         # Shields.io-style SVG badge
agentwise inspect .                                      # Per-server risk posture summary
agentwise inspect . --format json                        # Machine-readable inspect output

Baseline management

agentwise supports suppressing findings with expiry:

agentwise baseline init
agentwise baseline show
agentwise baseline add --rule AW-007 --server mcp-fetch --reason "trusted tool for now" --expires 2026-12-31
agentwise baseline remove --rule AW-007 --server mcp-fetch
agentwise baseline prune-expired

Parser compatibility

agentwise parses multiple MCP config shapes:

• mcpServers
• context_servers (e.g. Zed)
• lsp.{mcpServers|context_servers} nested blocks

Inspect mode

inspect gives a per-server posture view without changing the AW-* taxonomy:

agentwise inspect .
agentwise inspect ~/.mcp.json --format json

Inspect output includes transport type, auth/allowlist presence, package pinning, and risk tags such as remote_no_auth, unrestricted_network, and broad_filesystem.

Scoring

Every scan produces a security score from 0 to 100:

Grade	Score	Meaning
A	90-100	Excellent — minimal risk
B	80-89	Good — minor issues
C	70-79	Fair — some concerns
D	50-69	Poor — significant risks
F	0-49	Critical — immediate action needed

Scoring weights: Critical = -20, High = -10, Medium = -5, Low = -2.

CVE Database

agentwise ships with an embedded database of 22+ known MCP vulnerabilities, compiled at build time. Notable entries:

• CVE-2025-6514 — Command injection in MCP tool configs (CVSS 10.0)
• CVE-2026-2256 — Prompt-to-RCE via Shell tool in ms-agent (CVSS 10.0)
• CVE-2025-59536 — RCE via Claude Code project files (CVSS 9.8)
• CVE-2026-15503 — Container escape in mcp-server-docker (CVSS 9.6)
• CVE-2026-31024 — SQL injection in mcp-server-postgres (CVSS 9.1)
• CVE-2025-53110 — Path traversal in server-filesystem
• CVE-2025-68143 — Path traversal + argument injection in Git MCP

Update your local cache from OSV at any time:

agentwise update

Roadmap

• 12 detection rules (AW-001 through AW-012)
• Embedded CVE database (22+ entries)
• Live OSV + EPSS enrichment (--live)
• Supply chain analysis (--supply-chain)
• deps.dev dependency graph analysis
• Terminal, JSON, SARIF output
• GitHub Action
• Scoring system (0-100, A-F)
• Auto-discovery (agentwise scan --auto)
• Inspect mode (agentwise inspect)
• Custom rule DSL (YAML)
• Interactive TUI
• Auto-fix (agentwise fix)

Contributing

See CONTRIBUTING.md. The easiest way to contribute is adding new detection rules — each rule is a single file in src/rules/.

License

MIT License (LICENSE-MIT).

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Built by @brandonwise. Because your AI agents deserve better security than "auth": null.