linkedin_search
Search LinkedIn for people, companies, jobs, or posts. Supports filtering by keywords, location, industry, network distance, and more. Use linkedin.search_filters first to resolve filter keywords to LinkedIn parameter IDs.
This record as markdown: /tools/io-github-saloprj-dialogbrain/linkedin-search.md
What linkedin_search does on Dialogbrain
AI agents call linkedin_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 |
|---|---|---|---|
api | string | — | LinkedIn product to search with |
url | string | — | Direct LinkedIn search URL (alternative to keyword/filter search) |
role | string | — | Role/title filter |
limit | integer | — | Maximum results to return |
category | string | — | What to search for |
industry | array | — | Industry filter IDs |
keywords | string | — | Search keywords |
location | array | — | Location filter IDs (use linkedin.search_filters to resolve) |
has_job_offers | boolean | — | Filter for people with job offers |
network_distance | string | — | Connection degree: F=1st, S=2nd, O=3rd+ |
Parameters from the server's own tool schema.
Why linkedin_search is rated Low
This tool retrieves and queries data from LinkedIn without side effects. It performs a search operation to find information matching specified criteria (keywords, location, industry, network distance). No data creation, modification, deletion, or code execution is involved. The tool is purely informational and read-only in nature.
From the tool's definition Tool description explicitly states 'Search LinkedIn' with filtering capabilities. The term 'search' combined with read-only operations (finding people, companies, jobs, posts) with no mention of modification, deletion, or execution of actions.
Risk signalsAccepts URL/endpoint input (url) · High parameter count (10 properties)
Attacks that exploit this kind of access
The rule that runs linkedin_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 linkedin_search, this is the rule to start with:
linkedin_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 linkedin_search call is checked against it from then on.
Questions about linkedin_search
Search LinkedIn for people, companies, jobs, or posts. Supports filtering by keywords, location, industry, network distance, and more. Use linkedin.search_filters first to resolve filter keywords to LinkedIn parameter IDs. It is categorised as a Read tool in the Dialogbrain MCP Server, which means it retrieves data without modifying state.
linkedin_search accepts 10 parameters: api, url, role, limit, category, industry, keywords, location, has_job_offers, network_distance. 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 linkedin_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.
linkedin_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 linkedin_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 linkedin_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.
linkedin_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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