Perform deep research across multiple search terms using ONLY DuckDuckGo. Aggregates results from multiple DuckDuckGo searches, scores them by relevance, and returns the most relevant content with duplicates removed. Args: search_terms (List[str]): List of search terms to research. The LLM should...
AI agents call deep_research_ddgs to retrieve information from Mcp Local Rag without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This is a search and data retrieval tool. It queries DuckDuckGo, aggregates results, and returns information. There are no side effects, no data modification, no code execution, and no irreversible actions. The tool is purely informational and read-only in nature.
From the tool's definition Tool description states it "Perform[s] deep research across multiple search terms" and "Aggregates results from multiple DuckDuckGo searches, scores them by relevance, and returns the most relevant content." The operations are queries (search) and aggregation…
Documented attack patterns abuse exactly the kind of access deep_research_ddgs gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Local Rag, and nothing reaches the server without passing your rules. This is the rule we recommend for deep_research_ddgs:
{
"version": "1",
"default": "deny",
"tools": {
"deep_research_ddgs": {}
}
}deep_research_ddgs is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Perform deep research across multiple search terms using ONLY DuckDuckGo. Aggregates results from multiple DuckDuckGo searches, scores them by relevance, and returns the most relevant content with duplicates removed. Args: search_terms (List[str]): List of search terms to research. The LLM should provide multiple related search queries for comprehensive coverage. num_results_per_term (int): Number of results to fetch per search term. top_k_per_term (int): Number of top scored results to keep per search term. include_urls (bool): Whether to include URLs in the results. Returns: Dict containing aggregated research results from all search terms (DuckDuckGo only), with duplicates removed. It is categorised as a Read tool in the Mcp Local Rag MCP Server, which means it retrieves data without modifying state.
Register the Mcp Local Rag MCP server in PolicyLayer and add a rule for deep_research_ddgs: 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 Local Rag. Nothing to install.
deep_research_ddgs 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 deep_research_ddgs 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 deep_research_ddgs. 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.
deep_research_ddgs is provided by the Mcp Local Rag MCP server (nkapila6/mcp-local-rag). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 5 Mcp Local Rag tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
5 Mcp Local Rag tools catalogued and risk-classified — across an index of 42,500+ MCP servers.