generect-mcp

Count matching companies (free)

count_companies

Read-onlyIdempotent

How many companies match an ICP, and what pulling them would cost. FREE — this call never spends credits. Call this before search_companies. As with count_leads, a realtime count costs $0.02 and is never run implicitly.

Input Schema

TableJSON Schema

Name	Required	Description
`mode`	No	Data mode. "database" = cached, sub-second, cheaper, free counts, core filters only. "realtime" = live LinkedIn lookup, 5–60s, pricier, supports every filter. "auto" (default) tries database first and only escalates to realtime if a filter you passed is unsupported there — an escalation is reported in the response. Pick "database" explicitly when you only need a size estimate and cost matters more than freshness.
`keywords`	No	Free-text keywords across name/description/specialties — realtime only: using it forces the pricier live mode.
`locations`	No	HQ locations — cities, states or countries.
`headcounts`	No	Size buckets. Allowed ONLY: "1-10","11-50","51-200","201-500","501-1000","1001-5000","5001-10000","10 000+".
`industries`	No	Company industries. Must match Generect industry names exactly (e.g. "Software Development"); unknown names are rejected with HTTP 400.
`timeout_ms`	No	Request timeout in milliseconds.
`exclude_ids`	No	Exclude companies by LinkedIn id/URN.
`technologies`	No	Technologies the company uses — realtime only: using it forces the pricier live mode.
`company_names`	No	Restrict to specific company names — realtime only: using it forces the pricier live mode.
`company_types`	No	Company types: "Public Company","Privately Held","Non Profit","Government Agency","Educational", …
`revenues_range`	No	Annual revenue range, single object {min,max} — realtime only: using it forces the pricier live mode.
`sub_industries`	No	Expand each selected industry to its sub-industries as well (broadens the match).
`exclude_domains`	No	Exclude companies by domain (e.g. existing customers).
`linkedins_links`	No	Specific LinkedIn company URLs — realtime only: using it forces the pricier live mode.
`headcount_growth`	No	Headcount growth in percent — realtime only: using it forces the pricier live mode.
`num_of_followers`	No	LinkedIn follower buckets: "1-50","51-100","101-1000","1001-5000","5001+" — realtime only: using it forces the pricier live mode.
`exclude_locations`	No	HQ locations to exclude.
`get_max_companies`	No	DEPRECATED — accepted but ignored. Always on now: search responses include results_count without asking.
`exclude_industries`	No	Industries to exclude.
`hiring_on_linkedin`	No	Only companies actively hiring — realtime only: using it forces the pricier live mode.
`fallback_from_leads`	No	DEPRECATED — accepted but ignored. Removed. It fabricated lead-derived name aggregates and cost an extra billable query.
`department_headcount`	No	Department size, e.g. {"name":"engineering","min":10,"max":100} — realtime only: using it forces the pricier live mode.
`allow_unlisted_values`	No	Escape hatch for the local vocabulary check — see the lead-side field of the same name.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`fix`	No
`why`	No
`cost`	No
`mode`	No
`advice`	No
`status`	No
`options`	No
`test_mode`	No
`results_count`	No
`needs_realtime`	No
`test_mode_notice`	No
`next_step_estimate`	No
`vocabulary_warnings`	No
`blocked_by_vocabulary`	No
`deprecated_params_ignored`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 24, 2026

addedInput schema / properties / allow_unlisted_values

Added value: +{
+  "description": "Escape hatch for the local vocabulary check — see the lead-side field of the same name.",
+  "type": "boolean"
+}

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "advice": {
+      "type": "string"
+    },
+    "blocked_by_vocabulary": {
+      "$ref": "#/properties/vocabulary_warnings"
+    },
+    "cost": {
+      "additionalProperties": false,
+      "properties": {
+        "amount_charged_usd": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "billed": {
+          "type": "string"
+        },
+        "note": {
+          "type": "string"
+        },
+        "operation": {
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "deprecated_params_ignored": {
+      "additionalProperties": {
+        "type": "string"
+      },
+      "type": "object"
+    },
+    "fix": {
+      "type": "string"
+    },
+    "mode": {
+      "type": "string"
+    },
+    "needs_realtime": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "next_step_estimate": {},
+    "options": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "results_count": {
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "status": {
+      "type": "string"
+    },
+    "test_mode": {
+      "type": "boolean"
+    },
+    "test_mode_notice": {
+      "type": "string"
+    },
+    "vocabulary_warnings": {
+      "type": "array"
+    },
+    "why": {
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

AddedSep 10, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, so the bar for adding behavioral context is lower. The description adds valuable cost transparency beyond annotations: 'FREE — this call never spends credits' and 'a realtime count costs $0.02 and is never run implicitly'. This is useful, non-obvious behavior that helps the agent make cost-aware decisions.

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 sentences with zero filler. The first sentence front-loads the core purpose and cost, the second adds the free guarantee, and the third gives the ordering guidance. Every clause earns its place; no redundant phrasing.

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

Completeness5/5

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

Given the output schema exists and the input schema is fully documented, the description needs only to cover the non-schema context. It covers the critical decision factors: cost (free vs $0.02), the recommended call order, and the fact that realtime is never implicit. This is complete for an agent to correctly choose and invoke the tool.

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?

Schema description coverage is 100%, so the input schema already documents all 23 parameters with rich detail (including which ones force realtime mode). The description itself adds no parameter-level semantics beyond the schema, so the baseline of 3 is appropriate. No additional parameter meaning is provided.

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

Purpose5/5

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

The description states a specific verb and resource: 'How many companies match an ICP', clearly distinguishing it from search_companies (which would return records) and count_leads (which counts leads). The first sentence also adds the unique value of 'what pulling them would cost', making the tool's role unmistakable.

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

Usage Guidelines4/5

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

Explicitly gives the primary use case: 'Call this before search_companies', which is clear and actionable. It also references count_leads as a sibling for cost behavior, but does not explicitly state when to prefer count_leads over this tool or vice versa. The ordering guidance is strong, and cost implications are mentioned, so this is above average but not a full 5.

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

All generect-mcp tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.