numertel

Sprawdź numer telefonu (PL)

check_phone_number

Read-onlyIdempotent

Sprawdź reputację polskiego numeru telefonu. UŻYJ, gdy użytkownik pyta: kto dzwonił, czy numer to spam/oszustwo, czy telefon rzekomo z banku lub urzędu jest prawdziwy. Zwraca operatora z zakresów UKE (z notą o przenośności MNP), etykietę ryzyka z opinii, status w wykazie DNO UKE (połączenie przychodzące z numeru DNO jest sfałszowane — spoofing), wpis z Białej Listy oficjalnych infolinii i liczniki zgłoszeń. Dane: numertel.pl.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`number`	Yes	Polski numer w formacie 9 cyfr, np. 510100100 (akceptowane +48 i spacje — zostaną usunięte)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes
`e164`	Yes
`is_dno`	Yes
`number`	Yes
`dno_note`	No
`operator`	No
`score_avg`	No
`whitelist`	No
`spam_label`	Yes
`attribution`	Yes
`number_type`	No
`operator_note`	No
`sightings_30d`	No
`total_opinions`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed2 schema fields changedJun 12, 2026

changedInput schema / properties / number / description

Previous value: -"Polski numer: 9 cyfr (np. 500100200). Akceptowane +48 i spacje, zostaną usunięte."New value: +"Polski numer w formacie 9 cyfr, np. 510100100 (akceptowane +48 i spacje — zostaną usunięte)"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "attribution": {
+      "type": "string"
+    },
+    "dno_note": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "e164": {
+      "type": "string"
+    },
+    "is_dno": {
+      "type": "boolean"
+    },
+    "number": {
+      "type": "string"
+    },
+    "number_type": {
+      "type": "string"
+    },
+    "operator": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "operator_note": {
+      "type": "string"
+    },
+    "score_avg": {
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "sightings_30d": {
+      "type": "integer"
+    },
+    "spam_label": {
+      "enum": [
+        "brak_danych",
+        "raczej_bezpieczny",
+        "podejrzany",
+        "niebezpieczny",
+        "dno_spoofing"
+      ],
+      "type": "string"
+    },
+    "total_opinions": {
+      "type": "integer"
+    },
+    "url": {
+      "type": "string"
+    },
+    "whitelist": {
+      "properties": {
+        "institution": {
+          "type": "string"
+        },
+        "label": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "verified_on": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "institution",
+        "verified_on"
+      ],
+      "type": [
+        "object",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "number",
+    "e164",
+    "spam_label",
+    "total_opinions",
+    "is_dno",
+    "url",
+    "attribution"
+  ],
+  "type": "object"
+}

First observedJun 11, 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, openWorldHint, and idempotentHint. The description adds valuable context beyond annotations by detailing the exact data returned (operator, risk label, DNO status, white list, counters) and explains a nuanced behavior: DNO numbers indicate spoofing. It also cites the data source (numertel.pl), which is useful for trust assessment. This goes beyond a mere statement of safety.

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?

The description is compact, using two sentences to convey purpose, usage triggers, and output details. It is front-loaded with the action ('Sprawdź reputację') and organized logically: action first, then when to use, then return elements. Every clause adds relevant information without redundancy or fluff.

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?

For a single-parameter read-only lookup tool with a rich output schema and strong annotations, the description covers all necessary aspects: what the tool does, when to use it, what it returns, and even a caveat about DNO/spoofing. It is comprehensive enough for an agent to select and invoke the tool correctly without additional context.

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 schema covers 100% of parameter semantics with a description for 'number' that mentions format, accepted +48 prefix, and spaces being removed. The tool description adds little extra beyond restating that it handles Polish numbers, since the schema already provides detailed formatting guidance. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 clearly states the tool's function: 'Sprawdź reputację polskiego numeru telefonu' (check the reputation of a Polish phone number). It also lists specific user queries that should trigger use, such as 'kto dzwonił' (who called) or 'czy numer to spam/oszustwo' (is the number spam/scam), which distinguishes it from sibling tools like check_scam_domain and find_official_number.

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?

The description explicitly provides when-to-use guidance: 'UŻYJ, gdy użytkownik pyta: kto dzwonił, czy numer to spam/oszustwo, czy telefon rzekomo z banku lub urzędu jest prawdziwy.' This is clear and actionable. However, it does not explicitly mention when not to use this tool or name alternative tools, though the sibling list and the described features imply appropriate use cases.

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

All numertel tools Inspect

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TDQS

A4.1/5.0

Disambiguation3/5

Some tools overlap in functionality: check_phone_number and check_scam_domain both accept phone numbers, and search and find_official_number both return official numbers. The descriptions differentiate them, but an agent might be unsure which tool is best for a given query.

Naming Consistency2/5

Tool names follow mixed conventions: check_phone_number and check_scam_domain use verb_noun, fetch and search are bare verbs, recent_scam_domains is adjective_noun, and spam_weather is noun_noun. There is no consistent naming pattern across the set.

Tool Count5/5

With 7 tools, the set is well-scoped for a phone and scam reputation service. Each tool has a distinct role, and the count feels neither sparse nor bloated.

Completeness5/5

The tool surface covers the domain comprehensively: phone number reputation, scanning suspicious messages, finding official numbers, listing recent scam domains, and providing aggregate statistics. There are no obvious dead ends or missing core operations.

Sprawdź numer telefonu (PL)

Input Schema

Output Schema

Schema Changelog

TDQS

Glama MCP Gateway

TDQS

Resources