search_docs
Search the exchangerate.dev FAQ corpus via BM25. Returns the top-K matching questions and answers with relevance scores. Use before answering how-to / pricing / data-sourcing questions so you cite the canonical text instead of guessing from training data.
This record as markdown: /tools/dev-exchangerate-mcp/search-docs.md
What search_docs does on Exchangerate Dev
AI agents call search_docs to retrieve information from Exchangerate Dev 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 |
|---|---|---|---|
limit | integer | — | |
query | string | Yes |
Parameters from the server's own tool schema.
Why search_docs is rated Low
This tool performs a straightforward information retrieval operation (BM25 search) against a FAQ corpus. It queries documentation and returns results without side effects, data modification, code execution, or financial impact. The search is read-only, non-destructive, and low-risk even if misused by an AI agent, as it can only expose existing FAQ content.
From the tool's definition Tool name 'search_docs' and description explicitly states it 'Search[es]' and 'Returns the top-K matching questions and answers'—a retrieval operation with no modification or execution capability.
Attacks that exploit this kind of access
The rule that runs search_docs safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Exchangerate Dev, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For search_docs, this is the rule to start with:
search_docs 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 Exchangerate Dev, apply this rule, and every search_docs call is checked against it from then on.
Questions about search_docs
Search the exchangerate.dev FAQ corpus via BM25. Returns the top-K matching questions and answers with relevance scores. Use before answering how-to / pricing / data-sourcing questions so you cite the canonical text instead of guessing from training data. It is categorised as a Read tool in the Exchangerate Dev MCP Server, which means it retrieves data without modifying state.
search_docs accepts 2 parameters: limit, query. Required: query. The full parameter table on this page comes from the server's own tool schema.
Register the Exchangerate Dev MCP server in PolicyLayer and add a rule for search_docs: 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 Exchangerate Dev. Nothing to install.
search_docs 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 search_docs 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 search_docs. 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.
search_docs is provided by the Exchangerate Dev MCP server (https://api.exchangerate.dev/v1/mcp/). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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