API login authentication tool that uses environment variables for login credentials. Automatically extracts token from response and updates Authorization headers. Example: Call with optional baseUrl parameter to override default base URL
AI agents invoke api_login to trigger actions in MCP Project Standards Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool performs an external authentication operation against an API endpoint, triggers network requests, and has side effects by automatically extracting and updating Authorization headers (modifying state). It's not a simple read — it initiates an external operation and mutates session/header state.
From the tool's definition API login authentication tool that uses environment variables for login credentials. Automatically extracts token from response and updates Authorization headers.
Documented attack patterns abuse exactly the kind of access api_login gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP Project Standards Server, and nothing reaches the server without passing your rules. This is the rule we recommend for api_login:
{
"version": "1",
"default": "deny",
"tools": {
"api_login": {
"limits": [
{
"counter": "api_login_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}api_login stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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API login authentication tool that uses environment variables for login credentials. Automatically extracts token from response and updates Authorization headers. Example: Call with optional baseUrl parameter to override default base URL. It is categorised as a Execute tool in the MCP Project Standards Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the MCP Project Standards Server MCP server in PolicyLayer and add a rule for api_login: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches MCP Project Standards Server. Nothing to install.
api_login is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the api_login rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for api_login. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
api_login is provided by the MCP Project Standards Server MCP server (liliangshan/mcp-server-project-standards). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCP Project Standards Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
11 MCP Project Standards Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.