API Tools
safe4.ai
Provides pricing and payment authorization decisions for agent transactions.
ENDPOINT 1
https://api.safe4.ai/mcp
MCP server metadata
- Name
- safe4
- Version
- 1.29.1
Safe4 decides whether an AI agent's proposed payment should be allowed, by testing the purchase against the task the agent was actually given. The distinguishing case is a payment that is inside every budget, in an allowed category, and to an approved counterparty, and is still denied because it does not serve the task. safe4_price is free. safe4_authorize is settled per call in USDC over x402: call it without a payment to receive the price list, then again with a payment payload.
Known tools 2
CONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.safe4]
url = "https://api.safe4.ai/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"safe4": {
"type": "http",
"url": "https://api.safe4.ai/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: safe4
Remote MCP URL: https://api.safe4.ai/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"safe4": {
"url": "https://api.safe4.ai/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"safe4": {
"type": "http",
"url": "https://api.safe4.ai/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "safe4",
"transport": "streamable-http",
"url": "https://api.safe4.ai/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Trust Data Available
BuiltWith Trust API v2 evidence for safe4.ai was fetched 2026-08-29T17:31:10.299Z.
safe4.ai is assessed as Neutral: No suspicious signals found, but no strong positive signal either
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.