realestate-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool uniquely combines a property type (office, apartment, single/detached, row house) with a transaction type (trade or rent), resulting in 8 mutually exclusive purposes. No two tools overlap in function.
Naming Consistency5/5
All tools follow an identical get_<property_type>_<transaction_type> pattern with consistent snake_case. Property abbreviations are uniformly used across trade and rent variants, and transaction terms are consistent.
Tool Count5/5
The server uses 8 tools, which is well-scoped for a real estate price lookup service covering four property types and two transaction types. Each tool represents a distinct and necessary query combination.
Completeness5/5
The tool set comprehensively covers the main property types (apartment, office, single/detached, row house) and both major transaction types (sale and rent/lease). No obvious gaps exist in the stated domain of real estate transaction price lookup.
Average 3.2/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only implies a read-only query via '조회' but does not describe pagination, response format, rate limits, error handling, or any other behavioral traits, leaving the agent under-informed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, which makes it easy to parse, but it conveys only the bare purpose and borders on being a title rather than a functional description. It is concise yet under-specified.
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?
Given the lack of output schema and annotations, and the presence of pagination parameters, the description is not sufficiently complete. It does not explain what the tool returns, how to handle multiple pages, or any operational nuances, making it inadequate for robust agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description merely restates the two required parameters (지역코드+계약년월) already documented in the schema. It adds no meaning beyond the schema and does not compensate for the 50% schema description coverage, leaving pageNo and numOfRows unexplained.
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 purpose: '아파트 매매 실거래가 조회' (apartment sales transaction price inquiry) with a specific verb and resource. It also specifies the required query parameters (regionCode + dealYearMonth), which distinguishes it from siblings like get_apt_rent (rental) and other property-type tools.
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 description provides no explicit guidance on when to use this tool versus alternatives. It does not mention exclusions or refer to sibling tools; the only distinction is implicit in the name and the term '매매' (sales), leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says '조회' (inquiry), implying read-only, but omits pagination behavior, response format, and any rate limits. The presence of pageNo and numOfRows parameters is not mentioned, leaving the agent unaware of how to handle paged results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded phrase that efficiently communicates the core purpose and key inputs. It contains no fluff, though it is slightly too terse to serve as a full description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description provides minimal context. It does not explain what the response contains, how to handle pagination, or any defaults. Given the moderate complexity of four parameters, this is insufficient for an agent to invoke the tool reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers only the two required parameters; the pagination parameters pageNo and numOfRows have no descriptions. The description merely repeats the required parameters without adding additional meaning or format details, and fails to explain the undocumented pagination parameters.
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 retrieves officetel (오피스텔) jeonse/wolse actual transaction prices, and specifies the required inputs (region code and contract year month). This distinguishes it from siblings like get_offi_trade (officetel sales) and get_apt_rent (apartment rent).
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?
No explicit guidance is given on when to use this tool versus its siblings. The description only states the tool's function without mentioning use cases, alternatives, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. The description only mentions the query inputs and the fact that it is an inquiry; it does not disclose pagination behavior, response format, error handling, required permissions, or any other behavioral traits. This is essentially a restatement of the name without behavioral depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no fluff or redundant words. It is appropriately front-loaded with the core purpose. The brevity is a strength, though it leaves out behavioral details that would have been useful.
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?
Given no output schema, no annotations, and minimal description, the tool is not sufficiently complete for an AI agent to understand return values, pagination, or usage boundaries. The description is a one-liner that covers purpose but misses essential operational context, especially since sibling tools exist and could confuse selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (regionCode and dealYearMonth have descriptions; pageNo and numOfRows do not). The description adds no meaning beyond repeating the two required parameters and does not compensate for the undocumented parameters. It provides no semantic detail for pagination or parameter relationships.
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 purpose: 조회 (inquiry) of 단독/다가구 매매 실거래가 (single-family/multi-family housing sales transaction prices), with key required inputs (지역코드+계약년월). This is a specific verb+resource that distinguishes it from sibling tools like get_sh_rent (rent) and get_apt_trade (apartment trade).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the property type ('단독/다가구') and transaction type ('매매') in the description, but there is no explicit guidance on when to use this tool versus siblings (e.g., when to choose get_sh_trade vs get_apt_trade or get_sh_rent). It states the required inputs, which provides some context, but lacks exclusions or explicit alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden of disclosing behavior. It only states '조회' (inquiry), implying a read operation, but does not mention response format, pagination behavior, rate limits, error handling, or any side effects. This is a significant gap for a tool with four parameters and no output schema.
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 a single, compact Korean phrase that front-loads the core purpose and key inputs. Every word adds value, and there is no redundancy or filler.
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?
Given the tool's complexity (4 parameters, no annotations, no output schema), the description is incomplete. It lacks return value details, pagination defaults, and any differentiation from seven sibling tools. An agent would struggle to know what the response looks like or how to choose this tool over similar ones.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes regionCode and dealYearMonth with examples, and the description merely restates these two parameters without adding new meaning. It completely ignores pageNo and numOfRows, which are undocumented in the schema, so the description fails to compensate for the 50% schema coverage gap.
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 that the tool queries actual transaction prices for row houses and multi-family housing (연립다세대 매매 실거래가 조회), using a specific verb (조회) and resource. It also lists required inputs (지역코드+계약년월) and is unambiguous compared to sibling tools for apartments, officetels, and detached houses.
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 description offers no explicit guidance on when to use this tool versus its siblings (e.g., get_apt_trade, get_sh_rent). It only implies that the user needs a region code and contract year month, but does not state selection criteria, prerequisites, or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the query parameters and does not mention pagination, response format, data source, rate limits, or any side effects. Although '조회' (inquiry) hints at a read-only operation, this is insufficient for a 4-parameter tool with no output schema.
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 a single, clear sentence in Korean that immediately communicates the purpose and key dimensions. It is front-loaded with the core function and avoids any filler, making it highly efficient.
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?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the minimal description leaves significant gaps. It does not explain pagination behavior, response structure, or any prerequisites, making it incomplete for an agent to invoke correctly without additional assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description only mentions the two required parameters (regionCode and dealYearMonth), which are already described in the schema with examples. It does not add meaning for the pagination parameters pageNo and numOfRows, leaving them unexplained. With 50% schema description coverage, the description fails to compensate for the undocumented parameters.
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: retrieving actual transaction prices for apartment jeonse/wolse (rent) using region code and contract year-month. The phrase '아파트 전월세' (apartment rent) distinguishes it from sibling tools like get_apt_trade (apartment sales) and get_offi_rent (office rent), satisfying the specific verb+resource+scope criterion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for apartment rental price lookups by specifying the property type and transaction type, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. It offers clear context but no direct guidance on choosing among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only indicates a read-only inquiry ('조회') but provides no additional behavioral context such as pagination behavior, result limits, or error handling. This is a minimal disclosure that does not go beyond the basic operation.
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 a single, dense Korean sentence that front-loads the action and resource. It is appropriately sized for a simple query tool and contains no filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple, but the description leaves gaps: no guidance on paging parameters, no mention of return value structure (since no output schema exists), and no usage alternatives. The core purpose is clear, but the overall context is not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, and the description does not compensate for the undocumented pageNo and numOfRows parameters. It merely repeats the two required parameters already described in the schema, adding no new meaning or format details.
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: querying officetel sales transaction prices, with the key parameters region code and contract year month. It also distinguishes itself from siblings by specifying '오피스텔 매매' (officetel sales) as opposed to rent or other property types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its use case (officetel sales) but does not explicitly state when to use this vs. alternatives like get_offi_rent or get_apt_trade. The agent must infer from the tool name and sibling list, so guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. The verb '조회' clearly indicates a read-only operation, but the description does not disclose additional behavioral traits such as pagination behavior, rate limits, or authorization requirements. It also does not contradict any annotations.
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 a single, front-loaded sentence that clearly states the tool's purpose and key parameters. No wasted words.
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?
With no output schema, no annotations, and four parameters, the description is too brief. It does not explain the return value structure, pagination behavior, or expected usage patterns. An agent would lack critical information to correctly process the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%. The description mentions 지역코드 and 계약년월, but these are already covered by the schema descriptions. It does not add meaning for the undocumented pageNo and numOfRows parameters, nor does it explain pagination. The description adds minimal value beyond the schema.
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 verb '조회' (inquire) and the resource '단독/다가구 전월세 실거래가' (single/multi-household jeonse/wolse actual transaction price). This distinguishes it from sibling tools like get_apt_rent or get_sh_trade by housing type and transaction type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the housing type and transaction type (단독/다가구 전월세), but does not explicitly state when to use this tool vs alternatives or provide exclusions. The sibling list is not referenced.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The verb '조회' indicates a read/query operation, providing some transparency that this is a data retrieval tool with no mutation side effects. However, with no annotations, the description carries the full burden and does not disclose pagination behavior, response format, or any rate limits, leaving significant behavioral details undocumented.
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 a single, compact sentence that immediately states the purpose and key parameters. There is no redundant wording or filler, making it extremely efficient.
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?
Given that there is no output schema and no annotations, the description needs to explain what the tool returns, how pagination works, and any limitations. It does none of this, providing only the basic query intent. For a tool with 4 parameters and a potentially complex response, this is a significant gap.
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 50%, and the description reiterates the two required parameters (regionCode, dealYearMonth) but adds no new semantic details beyond what the schema already provides. It does not mention pageNo and numOfRows at all, so the 50% gap for these parameters remains uncompensated, though the core filtering params are highlighted.
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 uses the specific verb '조회' (query) and the resource '연립다세대 전월세 실거래가' (row house/multi-family rent transaction prices), which clearly distinguishes it from siblings like get_apt_rent, get_offi_rent, and get_rh_trade. It also specifies the key identifiers (지역코드+계약년월) in the description, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The implied usage is clear from the resource type: this tool is for row house/multi-family rent data, differentiating it from siblings. However, there is no explicit statement of when to use it over alternatives, no exclusions, and no mention of conditions or prerequisites.
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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