Social Fetch

Search LinkedIn organizations

linkedin_live_organizations_search_v2

Read-only

Search LinkedIn organizations by keyword. Returns a list (use cursor when paginated).

Input Schema

TableJSON Schema

Name	Required	Description
`trim`	No	Ignored if this tool does not support it.
`count`	No
`limit`	No	Alias for `count`. Prefer `count`.
`start`	No
`cursor`	No
`offset`	No	Ignored if this tool does not support it.
`context`	Yes	Describe the user's underlying goal in one sentence — not the tool you are calling.
`hasJobs`	No	Accepts a native boolean, or the string `true`/`false`/`1`/`0` (case-insensitive).
`keyword`	Yes
`industry`	No
`pageSize`	No	Alias for `count`. Prefer `count`.
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`maxResults`	No	Alias for `count`. Prefer `count`.
`geoEntityId`	No
`max_results`	No	Alias for `count`. Prefer `count`.
`headcountRange`	No
`conversation_id`	No	Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedSep 21, 2026

addedInput schema / properties / limit

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Alias for `count`. Prefer `count`."
+}

addedInput schema / properties / maxResults

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Alias for `count`. Prefer `count`."
+}

addedInput schema / properties / max_results

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Alias for `count`. Prefer `count`."
+}

addedInput schema / properties / offset

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}

addedInput schema / properties / pageSize

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Alias for `count`. Prefer `count`."
+}

addedInput schema / properties / trim

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}

AddedSep 19, 2026

TDQS

B3.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only and open-world behavior, so the description only needs to add operational traits. 'Returns a list (use cursor when paginated)' adds a concrete return shape and pagination mechanism that the annotations and schema do not convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with the core verb-resource statement first and pagination guidance second. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 17-parameter search tool with no output schema, this two-sentence description is too thin: it does not explain how count/start and cursor relate, what filters exist, or what the returned list entries look like. An agent would likely need to inspect the schema deeply and may still mishandle pagination semantics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaning for keyword and cursor ('use cursor when paginated'), but with 17 parameters and 59% schema description coverage, it leaves the filter parameters (industry, geoEntityId, headcountRange, hasJobs) and pagination parameters (count/start vs cursor) undocumented in prose. It is not misleading, just incomplete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('search'), resource ('LinkedIn organizations'), and search mode ('by keyword'), so an agent can tell it apart from exact-ID siblings like linkedin_live_organization_get_v2 or linkedin_live_organization_resolve_v2. It stops short of explicitly calling out those alternatives, so it does not quite earn a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The only usage instruction is to use cursor when paginated; there is no guidance on when to prefer this search tool over the many LinkedIn lookup/retrieval siblings (organization_get_v2, resolve_v2, batch_v2, similar_v2) or other search tools. Choosing among alternatives is left entirely to inference from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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Search LinkedIn organizations

Input Schema

Schema Changelog

TDQS

Glama MCP Gateway

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