tool_call
Dispatches to any tool in the catalogue. Most clients cap how many tools they will hold at once — Cursor drops everything past roughly forty across all servers combined — so only a core set is listed by default. Everything else is reachable here. Find a name with tool.search, check its shape with...
This record as markdown: /tools/com-fluentedi-tools/tool-call.md
What tool_call does on Tools
AI agents use tool_call to create or update resources in Tools, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Tools environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
args | object | — | Arguments for that tool. |
tool | string | Yes | Name of the tool to invoke. |
Parameters from the server's own tool schema.
Why tool_call is rated Medium
An AI agent can call tool_call faster than any human can review: one bad instruction and it creates or modifies resources in Tools by the hundred, each call as confident as the last.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs tool_call safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Tools, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For tool_call, this is the rule to start with:
tool_call stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Tools, apply this rule, and every tool_call call is checked against it from then on.
Questions about tool_call
Dispatches to any tool in the catalogue. Most clients cap how many tools they will hold at once — Cursor drops everything past roughly forty across all servers combined — so only a core set is listed by default. Everything else is reachable here. Find a name with tool.search, check its shape with tool.describe, then call it through this. It is categorised as a Write tool in the Tools MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
tool_call accepts 2 parameters: args, tool. Required: tool. The full parameter table on this page comes from the server's own tool schema.
Register the Tools MCP server in PolicyLayer and add a rule for tool_call: 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 Tools. Nothing to install.
tool_call is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the tool_call 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 tool_call. 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.
tool_call is provided by the Tools MCP server (https://fluentedi.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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