web__local_search
Multi-source web research with citations. Returns a synthesized answer with numbered [^1] markers and a citations array of {url, title, snippet, index}. Use for evidence-backed synthesis (competitive analysis, regulatory summary, whitepaper section). For quick fact lookups use web.search instead.
This record as markdown: /tools/io-github-saloprj-dialogbrain/web--local-search.md
What web__local_search does on Dialogbrain
AI agents call web__local_search to retrieve information from Dialogbrain 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 |
|---|---|---|---|
query | string | Yes | Research question. Specific scoped questions outperform vague keywords. |
language | string | — | Search language hint (BCP-47, e.g. 'en', 'ru'). Defaults to 'en'. The synthesis output language matches the query language regardless. |
num_sources | integer | — | How many top search results to fetch and synthesize (1-4, default 4). Lower = faster + cheaper, higher = more comprehensive. |
Parameters from the server's own tool schema.
Why web__local_search is rated Low
web__local_search retrieves and synthesizes information from web sources without any side effects. It reads data and returns citations, answers, and snippets—classic Read behavior. No data is modified, deleted, executed, or financially committed. The tool is explicitly positioned as an alternative to quick fact lookups with no capability to alter state.
From the tool's definition Tool description states it 'Returns a synthesized answer with numbered markers and a citations array' and is used for 'evidence-backed synthesis' and 'fact lookups'.
Attacks that exploit this kind of access
The rule that runs web__local_search safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dialogbrain, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For web__local_search, this is the rule to start with:
web__local_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 Dialogbrain, apply this rule, and every web__local_search call is checked against it from then on.
Questions about web__local_search
Multi-source web research with citations. Returns a synthesized answer with numbered [^1] markers and a citations array of {url, title, snippet, index}. Use for evidence-backed synthesis (competitive analysis, regulatory summary, whitepaper section). For quick fact lookups use web.search instead. It is categorised as a Read tool in the Dialogbrain MCP Server, which means it retrieves data without modifying state.
web__local_search accepts 3 parameters: query, language, num_sources. Required: query. The full parameter table on this page comes from the server's own tool schema.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for web__local_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 Dialogbrain. Nothing to install.
web__local_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 web__local_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 web__local_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.
web__local_search is provided by the Dialogbrain MCP server (https://api.dialogbrain.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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