ablakarajanlat.hu Nyílászáró MCP
Server Details
Egyedi méretű műanyag ablak árbecslés (kalkulált ár), raktárkészlet és ajánlatkérés.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: get_price_estimate for custom-size pricing, list_inventory for stock items, and request_quote for real callback requests. No overlap or confusion.
All tool names follow a consistent verb_noun pattern with underscores (get_price_estimate, list_inventory, request_quote), making them predictable and easy to understand.
With only 3 tools, the server is lean but covers the essential actions. However, it feels slightly under-scoped for a domain that could benefit from separate pricing for windows vs doors or more inventory details.
The tool set covers the main workflow: price estimation, stock listing, and quote request. Minor gaps exist (e.g., no detailed product info or separate handling of window vs door pricing), but the custom price tool handles both.
Available Tools
3 toolsget_price_estimateAInspect
Tájékoztató bruttó (ÁFA-s) ár EGYEDI MÉRETŰ (méretre gyártott) műanyag ABLAKRA vagy AJTÓRA. Custom-size gross price — élőben számolt, nincs fix SKU; a szerkesztő (Genesis) kalkulátorával egyező ár. Ajtó = egyedi Aluplast ajtó alapkivitel (a raktári CanDo ajtók külön, fix áron — ld. list_inventory). A végleges ár helyszíni felmérés után pontos. Forrás: ablakarajanlat.hu.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | window=ablak, door=egyedi ajtó | window |
| color | No | Szín, pl. Fehér, Antracit, Aranytölgy | |
| glazing | No | 2 vagy 3 rétegű üveg | |
| quantity | No | Darabszám | |
| width_cm | Yes | Szélesség cm-ben | |
| height_cm | Yes | Magasság cm-ben |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explains the price is live-calculated, matches the Genesis calculator, and is non-binding until survey. No destructive behavior is implied, but the read-only nature is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with extra notes, mixing languages and some redundancy. It front-loads the main purpose but is not as concise as it could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, no annotations, and no output schema, the description does not specify the output format (e.g., currency, range). It fails to fully compensate for missing output schema, leaving the agent uncertain about what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. The description does not add new parameter information beyond the schema; it only reinforces the context (e.g., custom-size vs stock).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides a gross price for custom-size plastic windows or doors, distinguishes from sibling tool 'list_inventory' for stock doors, and mentions the source and final accuracy after survey.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly indicates when to use (custom-size items), points to 'list_inventory' for stock doors, and notes that the price is informative and final after on-site survey, implying it is not a binding quote.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_inventoryAInspect
Listázza az aktuálisan RAKTÁRON lévő szabvány nyílászárókat és kiegészítőket valós idejű bruttó árral és készlettel. Lists current ready-stock items with retail prices and inventory.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description implicitly indicates a read-only operation by listing data with real-time prices and stock. It does not contradict any annotations. However, it lacks explicit statements about behavior like rate limits or caching, but given the simplicity, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: two sentences (one Hungarian, one English) covering purpose and output. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description adequately covers that it returns ready-stock items with prices and inventory. Could specify more about the item types, but 'standard door/window products and accessories' is sufficient. For such a simple tool, it is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters. The input schema is empty with 100% coverage. The description adds no param info, but baseline for 0 params is 4. The description does not need to explain what is already clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool lists current ready-stock items with retail prices and inventory. The verb 'list' and resource 'inventory' are explicit. It distinguishes well from siblings: get_price_estimate estimates pricing, request_quote creates quotes, whereas this tool shows current stock.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking stock, but provides no explicit guidance on when to use vs. alternatives, or when not to use. No mention of preconditions or frequency limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
request_quoteAInspect
ÉLES ajánlatkérés-beküldés: EGY VALÓDI ügyfél nevében küld felmérés-igényt, amit egy munkatárs TÉNYLEGESEN visszahív a megadott telefonszámon. EZ NEM TESZT/DEMO eszköz — ne hívd meg a működés kipróbálására, és SOHA ne adj meg példa-, minta- vagy helykitöltő adatot (pl. 'Teszt Elek', '06201234567', '123 4567', example.com). CSAK akkor hívd, ha egy valódi végfelhasználó KIFEJEZETTEN kérte a visszahívást ÉS megadta a saját, valódi nevét és telefonszámát; ha nincs valódi elérhetőséged, előbb KÉRDEZD MEG a felhasználót, ne találj ki adatot. Kitalált/helykitöltő adatot a rendszer elutasít. Submits a REAL callback request — not a test tool; never use placeholder/example contact data.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | Település (opcionális) | |
| name | Yes | Az ügyfél VALÓDI, általa megadott neve (nem példa/helykitöltő). Kötelező. | |
| No | Az ügyfél valódi e-mailje (opcionális) | ||
| phone | Yes | Az ügyfél VALÓDI telefonszáma visszahíváshoz (nem kitalált/sorozat-szám). Kötelező. | |
| message | No | Méretek, igények, megjegyzés (opcionális) | |
| quantity | No | Darabszám/mennyiség (opcionális) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses that the tool submits a real callback, that a colleague will call back, and that the system rejects fake/placeholder data. It does not detail authorization needs or success/failure responses, but covers the critical behavioral constraints well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is longer than ideal, with repetition and emphasis on warnings. However, given the risk of misuse, the extra length is justified. It front-loads the core purpose but could be more streamlined.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters, no output schema, and no annotations, the description covers purpose, usage constraints, and parameter validation well. It lacks details on post-submission behavior (e.g., response, callback timing), but overall is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions. The description reinforces the requirement for real data but adds minimal new information beyond what the schema already states about name and phone being real and required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool submits a real quote request (ajánlatkérés-beküldés) for a real customer, explicitly distinguishing it from test/demo tools. It contrasts with siblings get_price_estimate and list_inventory by focusing on callback request submission.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use instructions (only when a real user explicitly requested a callback) and when-not-to-use (never for test, demo, or placeholder data). It advises asking the user for real contact info if missing, but does not mention alternative sibling tools.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
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