A
licenseNot graded
qualityD
maintenanceA server that enables AI models to access Kakao Map features (place search, address lookup, route finding) and Daum search services (web, image, blog, cafe) through Model Context Protocol.
17
MIT
MCP Naver Maps
by yunkee-lee
MCP Naver 地图
MCP 连接到Naver Maps API和Naver Search API 。 API 的应用程序是 API 的应用程序 (로컬) 和 MCP 的应用程序。
它目前支持以下 API：
先决条件
开始之前，请确保已安装以下软件：
Python： 3.13 或更高版本
**uv：**您可以在此处找到安装说明。
**Naver 云平台账户：**您需要 Naver 地图服务的 API 凭证（客户端 ID 和客户端密钥）。您可以从Naver 云平台控制台获取这些信息。
**Naver Develoeprs 帐户：**您需要 Naver Developers API 的 API 凭证（客户端 ID 和客户端密钥）。您可以从Naver Developers获取这些凭证。
Related MCP server: MCP TMAP Server
配置
**创建
.env文件：**在项目根目录中创建一个文件。**添加 API 凭据：**编辑
.env文件并添加您的 Naver Maps API 凭据和 Naver Developers API 凭据。NAVER_MAPS_CLIENT_ID="YOUR_NAVER_MAPS_CLIENT_ID" NAVER_MAPS_CLIENT_SECRET="YOUR_NAVER_MAPS_CLIENT_SECRET" NAVER_CLIENT_API="YOUR_NAVER_CLIENT_API" NAVER_CLIENT_SECRET="YOUR_NAVER_CLIENT_SECRET"请检查
src/mcp_naver_maps/naver_maps_client.py来验证所需的确切环境变量名称。
运行 MCP
**同步依赖项：**在终端中导航到项目根目录并运行以下命令。这将创建一个虚拟环境（如果不存在）并安装
pyproject.toml中指定的所有依赖项。uv sync**运行：：**您可以使用
uv运行 MCP 服务器。uv run src/mcp_naver_maps为了发展，
source .venv/bin/activate mcp dev src/mcp_naver_maps/server.py
Available Tools
2 toolsgeocodeB
Searches for address information related to the entered address.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | address to search for | |
| language | No | language used in response | kor |
TDQS
B3.1/5.0
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. While 'searches' implies a read-only operation, it doesn't specify details like rate limits, authentication needs, error handling, or what 'address information' includes (e.g., coordinates, formatted address). This is a significant gap for a tool with no annotation coverage.
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, efficient sentence that directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, making it easy to parse quickly. Every word earns its place.
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?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and output format. Without an output schema, the description should ideally hint at what 'address information' includes, but it doesn't, leaving gaps in completeness.
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 input schema has 100% description coverage, with clear documentation for both parameters (address and language). The description adds no additional meaning beyond the schema, such as examples or usage notes. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.
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 clearly states the tool's purpose: 'Searches for address information related to the entered address.' This specifies the verb ('searches for') and resource ('address information'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from the sibling tool 'localSearch', which might have overlapping functionality.
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 guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'localSearch' or any other context for usage, such as prerequisites or exclusions. This leaves the agent with no explicit direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
localSearchC
Searches for places registered with Naver's local service.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | query used for search | |
| display | No | number of search results to display in response | |
| sort | No | sorting method. random: sorted by correctness. comment: sorted by a number of reviews (descending) | random |
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't mention rate limits, authentication requirements, error conditions, response format, or whether this is a read-only operation. For a search tool with external API dependencies, this is insufficient behavioral context.
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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a search tool and gets straight to the point with zero wasted text.
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 search tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the response contains (e.g., place details, addresses, ratings), doesn't mention API limitations or authentication, and provides no guidance relative to the sibling tool. The agent would need to guess about important operational aspects.
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 no parameter information beyond what's already in the schema, which has 100% coverage. The schema fully documents all three parameters with descriptions, constraints, and defaults. The baseline score of 3 reflects adequate schema coverage without additional value from the description.
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 clearly states the action ('Searches for') and resource ('places registered with Naver's local service'), providing a specific purpose. However, it doesn't differentiate from the sibling tool 'geocode' which likely handles location-based searches, leaving room for ambiguity about when to use each.
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 guidance on when to use this tool versus alternatives. With a sibling tool 'geocode' available, there's no indication of whether this tool is for general place searches versus coordinate-based lookups, leaving the agent to guess about appropriate contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
B3.1/5.0
Disambiguation5/5
The two tools have clearly distinct purposes: geocode handles address-to-coordinate conversion, while localSearch finds registered places. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the task.
Naming Consistency5/5
Both tools follow a consistent naming pattern using camelCase (geocode, localSearch) with descriptive verb-noun structures. The naming is uniform and predictable across the set.
Tool Count2/5
With only two tools, the server feels under-scoped for a maps domain. While geocoding and local search are core functions, typical maps services include additional operations like routing, place details, or reverse geocoding, making this set appear incomplete.
Completeness2/5
For a maps server, there are significant gaps in coverage. Missing tools for routing, reverse geocoding, place details, or map visualization limit an agent's ability to handle common mapping workflows, leading to potential dead ends in tasks.
Maintenance
ActivityInactive
ResponsivenessNo issues
Resources
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