call_tool
Runs ONE read-only AINumbers tool that is not in your tool list. tools/list is paginated (13 pages, 722 tools) and many hosts read only the first page; this is the door to the rest. Pass { name: "<exact mcp_name>", arguments: { ... } } — the target's own inputSchema is validated and its result is...
This record as markdown: /tools/postoaklabs-ainumbers-mcp-apps/call-tool.md
What call_tool does on Ainumbers Mcp Apps
AI agents invoke call_tool to trigger actions in Ainumbers Mcp Apps. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | Yes | Exact mcp_name of the tool to run (e.g. "recompute_payment_waterfall"). Use find_tool/describe_tool to get it; this takes the exact name only. |
arguments | object | — | The target tool's own arguments object, exactly as you would pass it on a direct call. Omit for a no-argument tool. |
Parameters from the server's own tool schema.
Why call_tool is rated High
Dispatches arbitrary tool calls by name; broad execution surface despite read-only claim.
From the tool's definition Runs ONE read-only AINumbers tool not in your tool list
Attacks that exploit this kind of access
The rule that runs call_tool safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ainumbers Mcp Apps, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For call_tool, this is the rule to start with:
call_tool 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Ainumbers Mcp Apps, apply this rule, and every call_tool call is checked against it from then on.
Questions about call_tool
Runs ONE read-only AINumbers tool that is not in your tool list. tools/list is paginated (13 pages, 722 tools) and many hosts read only the first page; this is the door to the rest. Pass { name: "<exact mcp_name>", arguments: { ... } } — the target's own inputSchema is validated and its result is returned verbatim, including execution_hash, so a dispatched call and a direct call are byte-identical. Get a name from find_tool (single calculators), find_chain (workflows) or describe_tool (exact schema). Read-only tools only: anything that issues a credential, stamps an anchor or reaches the network is refused here and must be called directly so your host can approve it. It is categorised as a Execute tool in the Ainumbers Mcp Apps MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
call_tool accepts 2 parameters: name, arguments. Required: name. The full parameter table on this page comes from the server's own tool schema.
Register the Ainumbers Mcp Apps MCP server in PolicyLayer and add a rule for call_tool: 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 Ainumbers Mcp Apps. Nothing to install.
call_tool 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 call_tool 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 call_tool. 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.
call_tool is provided by the Ainumbers Mcp Apps MCP server (postoaklabs/ainumbers-mcp-apps). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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