MCPVetter
Audit your MCP servers for poisoned tools and leaked secrets, and check AI-generated code for flaws.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
claude mcp add --transport http mcpvetter 'https://mcpvetter.com/mcp'
{
"mcpServers": {
"mcpvetter": {
"type": "http",
"url": "https://mcpvetter.com/mcp"
}
}
}
mcpvetterclaude mcp add mcpvetter -e 'MCPVETTER_API_KEY=<your mcpvetter_api_key>' -- npx -y mcpvetter@0.1.3 serve
{
"mcpServers": {
"mcpvetter": {
"command": "npx",
"args": [
"-y",
"mcpvetter@0.1.3",
"serve"
],
"env": {
"MCPVETTER_API_KEY": "<your mcpvetter_api_key>"
}
}
}
}
Environment variables
MCPVETTER_API_KEYsecret Optional. Unlocks review_code, labs and patterns (free tier at mcpvetter.com/account). Scanner tools work without it.
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
mcpvetter
Audit the MCP servers your AI assistant uses: leaked secrets, unpinned or look-alike packages, risky launch commands, unencrypted remote servers, over-broad file access, poisoned tool descriptions, hidden Unicode, tool shadowing, and silent tool changes.
npx mcpvetter scan # discover + static scan, offline
npx mcpvetter scan --live # also read each server's tool descriptions (asks first)
Local, no account, no telemetry. A static scan reads your MCP config files and nothing else. It never changes a config file.
What a finding looks like
■ github
[HIGH] Plain-text secret in MCP config MCP-SECRET-001 · confidence high · static
server: github file: .mcp.json
Evidence: env GITHUB_PERSONAL_ACCESS_TOKEN=ghp_…[redacted 40 chars] (GitHub token)
Why it matters: Anything that can read this file, including other tools, backups, sync
folders, and anyone the file is shared or committed with, gets a working credential.
Fix: Rotate the credential first (removing it does not un-leak it), then reference it
from the environment or a secret store instead of the literal value. Claude Code and
Claude Desktop expand "${VAR}" in .mcp.json, Cursor expands "${env:VAR}", and VS Code
supports "${input:...}" prompts or an "envFile".
Every finding has a stable ID, separate severity and confidence, redacted evidence, a plain-English reason, and a concrete fix. What each rule checks, and how, is published at mcpvetter.com/rules and in src/scanner/rules.
Clients discovered
Claude Code (~/.claude.json, .mcp.json), Claude Desktop, Cursor (~/.cursor/mcp.json, .cursor/mcp.json), VS Code (mcp.json, settings.json, .vscode/mcp.json), Windsurf, Gemini CLI. Or pass --config <file>.
Commands
mcpvetter scan [--live] [--yes] [--config <file>]... [--json [file]] [--summary] [--fail-on <severity>]
mcpvetter list inventory only
mcpvetter explain MCP-POISON-001 explain a finding
mcpvetter rules every rule and what it checks
mcpvetter suppress <ID> --server <name> --reason "<why>"
mcpvetter accept <server> --reason "<why>" accept a server's new tool fingerprint
mcpvetter serve run as a local MCP server (stdio)
Exit codes: 0 no findings at or above --fail-on (default high), 1 findings at or above it, 2 scan could not complete. Use it in CI as-is.
Suppressions are always listed in the report, so a shared report cannot hide them.
About --live
To read tool descriptions, MCPVetter has to start each stdio server, exactly as your AI client does every time it launches. It asks before each one, runs it with a minimal environment plus the env your config declares, and only calls initialize, tools/list, prompts/list, and resources/list. It never calls a tool. The first approved probe records a fingerprint of each server's tools in ~/.mcpvetter/fingerprints.json; later probes report any change (a "rug pull") with a before/after diff.
Inside your AI assistant
Claude Code:
claude mcp add mcpvetter -- npx -y mcpvetter@0.1.2 serve
Cursor / VS Code / Claude Desktop (mcpServers or servers):
{ "mcpServers": { "mcpvetter": { "command": "npx", "args": ["-y", "mcpvetter@0.1.2", "serve"] } } }
Then ask: "audit my MCP setup".
Free without an account: check_mcp_setup, explain_finding. With an API key (MCPVETTER_API_KEY, free tier available at mcpvetter.com/account): review_code, secure_pattern, start_lab, check_lab, team_posture. Code review runs on your machine; only rule IDs and counts are sent for your history. Plans: mcpvetter.com/pricing.
Privacy
- Static analysis runs on your machine. Without an API key, MCPVetter makes no network requests.
- With an API key, only rule IDs, severities, and counts are sent. Never code, evidence, file paths, or server names.
- Reports redact secret values by default.
License
MIT
Frequently asked questions
What is MCPVetter?
Audit your MCP servers for poisoned tools and leaked secrets, and check AI-generated code for flaws.
How do I install MCPVetter?
It runs as a remote server. In Claude Code: claude mcp add --transport http mcpvetter 'https://mcpvetter.com/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.
Does MCPVetter need an API key?
Yes. It expects MCPVETTER_API_KEY, which you set in its configuration.
Is MCPVetter open source?
Yes. Its code is on GitHub under the MIT license.
Who maintains MCPVetter?
It is published by jaablon. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.