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Credential isolation for AI agents. Inject secrets at the network boundary.
Credential isolation for AI agents. Inject secrets at the network boundary.
Set these up before or after installing:
Environment variable: AEGIS_MASTER_KEY
Environment variable: AEGIS_SALT
Environment variable: AEGIS_DATA_DIR
Environment variable: AEGIS_PORT
Environment variable: AEGIS_LOG_LEVEL
Environment variable: AEGIS_LOG_FORMAT
Environment variable: AEGIS_VAULT
Environment variable: AEGIS_REQUIRE_AGENT_AUTH
Environment variable: AEGIS_POLICY_MODE
Environment variable: AEGIS_POLICIES_DIR
Environment variable: AEGIS_METRICS
Unverified package source
We couldn't verify that the installable package matches the reviewed source code. Proceed with caution.
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-getaegis-aegis": {
"env": {
"AEGIS_PORT": "your-aegis-port-here",
"AEGIS_SALT": "your-aegis-salt-here",
"AEGIS_VAULT": "your-aegis-vault-here",
"AEGIS_METRICS": "your-aegis-metrics-here",
"AEGIS_DATA_DIR": "your-aegis-data-dir-here",
"AEGIS_LOG_LEVEL": "your-aegis-log-level-here",
"AEGIS_LOG_FORMAT": "your-aegis-log-format-here",
"AEGIS_MASTER_KEY": "your-aegis-master-key-here",
"AEGIS_POLICY_MODE": "your-aegis-policy-mode-here",
"AEGIS_POLICIES_DIR": "your-aegis-policies-dir-here",
"AEGIS_REQUIRE_AGENT_AUTH": "your-aegis-require-agent-auth-here"
},
"args": [
"-y",
"@aegis/dashboard"
],
"command": "npx"
}
}
}This is a well-architected security-focused MCP server for credential isolation. The code demonstrates good security practices with encrypted credential storage, domain restrictions, and comprehensive audit logging. No significant security vulnerabilities were found. Supply chain analysis found 3 known vulnerabilities in dependencies. Package verification found 1 issue (1 critical, 0 high severity).
Scanned 4 files · 7 findings
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