tool_search
Searches every tool by name, summary, description and keywords, and returns the closest matches with their endpoints and parameters. Use this instead of loading the whole catalogue: describe the job ("check whether a shipment is late", "fix broken JSON", "validate a barcode check digit") and call...
This record as markdown: /tools/com-fluentedi-tools/tool-search.md
What tool_search does on Tools
AI agents call tool_search to retrieve information from Tools without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
q | string | Yes | What you are trying to do, in plain language. |
limit | integer | — | Maximum matches to return. |
detail | boolean | — | Include full parameter schemas and worked examples for each match. |
Parameters from the server's own tool schema.
Why tool_search is rated Low
Even though tool_search only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs tool_search 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_search, this is the rule to start with:
tool_search is read-only, so it stays allowed. 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_search call is checked against it from then on.
Questions about tool_search
Searches every tool by name, summary, description and keywords, and returns the closest matches with their endpoints and parameters. Use this instead of loading the whole catalogue: describe the job ("check whether a shipment is late", "fix broken JSON", "validate a barcode check digit") and call what comes back. Each result says why it matched, so a wrong match is obvious rather than plausible. It is categorised as a Read tool in the Tools MCP Server, which means it retrieves data without modifying state.
tool_search accepts 3 parameters: q, limit, detail. Required: q. 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_search: 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_search is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the tool_search 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_search. 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_search 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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