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search.semantic.similar

Find web pages semantically similar to a given URL — discover related content, competitors, alternatives without knowing what to search for. Unique capability for research agents (Exa)

SERVERApibase SOURCEapibase-mcp-client
Low RISK CLASS
Category Read
Parameters 51 required
Recommended Allowedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-whiteknightonhorse-apibase/search.semantic.similar.md

What search.semantic.similar does on Apibase

AI agents call search.semantic.similar to retrieve information from Apibase without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

ParameterTypeRequiredDescription
url string Yes Reference URL — Exa finds pages semantically similar to this one
num_results integer — Number of similar pages (default 10, max 25)
include_text boolean — Include full extracted page text (default false)
start_published_date string — Only include similar pages published after this date (ISO format)
exclude_source_domain boolean — Exclude results from same domain as input URL (default true)

Parameters from the server's own tool schema.

Why search.semantic.similar is rated Low

Queries and retrieves web content; no data modification, deletion, or side effects occur.

From the tool's definition Find web pages semantically similar to a given URL — discover related content

Risk signalsAccepts URL/endpoint input (url)

Questions about search.semantic.similar

What does the search.semantic.similar tool do? +

Find web pages semantically similar to a given URL — discover related content, competitors, alternatives without knowing what to search for. Unique capability for research agents (Exa). It is categorised as a Read tool in the Apibase MCP Server, which means it retrieves data without modifying state.

What parameters does search.semantic.similar accept? +

search.semantic.similar accepts 5 parameters: url, num_results, include_text, start_published_date, exclude_source_domain. Required: url. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on search.semantic.similar? +

Register the Apibase MCP server in PolicyLayer and add a rule for search.semantic.similar: 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 Apibase. Nothing to install.

What risk level is search.semantic.similar? +

search.semantic.similar is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit search.semantic.similar? +

Yes. Add a rate_limit block to the search.semantic.similar 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.

How do I block search.semantic.similar completely? +

Set action: deny in the PolicyLayer policy for search.semantic.similar. 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.

What MCP server provides search.semantic.similar? +

search.semantic.similar is provided by the Apibase MCP server (apibase-mcp-client). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

More on Apibase, and thousands of servers like it.

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