MCP Naver Maps
MCP 네이버 지도
MCP는 Naver Maps API 및 Naver Search API 에 연결됩니다. 네이버 지도 API와 검색 API에 (로컬) 연결하는 MCP 서버입니다.
현재 다음 API를 지원합니다.
필수 조건
시작하기 전에 다음 사항이 설치되어 있는지 확인하세요.
Python: 버전 3.13 이상
uv: 설치 지침은 여기에서 확인할 수 있습니다.
네이버 클라우드 플랫폼 계정: 네이버 지도 서비스를 사용하려면 API 자격 증명(클라이언트 ID 및 클라이언트 시크릿)이 필요합니다. 이 정보는 네이버 클라우드 플랫폼 콘솔 에서 확인할 수 있습니다.
네이버 개발자 계정: 네이버 개발자 API를 사용하려면 API 자격 증명(클라이언트 ID와 클라이언트 시크릿)이 필요합니다. 이 정보는 네이버 개발자 페이지 에서 받으실 수 있습니다.
Related MCP server: MCP TMAP Server
구성
.env파일을 만듭니다. 프로젝트 루트에 파일을 만듭니다.API 자격 증명 추가:
.env파일을 편집하여 Naver Maps API 자격 증명과 Naver Developers API 자격 증명을 추가합니다.지엑스피1
src/mcp_naver_maps/naver_maps_client.py확인하여 필요한 정확한 환경 변수 이름을 확인하세요.
MCP 실행
종속성 동기화: 터미널에서 프로젝트 루트 디렉터리로 이동하여 다음 명령을 실행하세요. 가상 환경이 없는 경우 생성되고
pyproject.toml에 지정된 모든 종속성이 설치됩니다.uv sync실행:
uv사용하여 MCP 서버를 실행할 수 있습니다.uv run src/mcp_naver_maps개발을 위해,
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.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | address to search for | |
| language | No | language used in response | kor |
TDQS
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.
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.
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.
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.
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.
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.
| 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
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.
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.
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.
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.
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.
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
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.
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.
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.
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
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Korean business registry, corporate info, parcel tracking, validation APIs
MCP server for Japan geodata: cadastral lot numbers (chiban) and reverse geocoding, for AI agents.
Geospatial intelligence with Mapbox APIs like geocoding, POI search, directions, isochrones, etc.
Geocoding, reverse geocoding, and places search for LatLng.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceA 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.17MIT
- AlicenseCqualityDmaintenanceA server that connects to SK TMAP API, providing access to public transit routing and geocoding functionality through a standardized interface.2MIT
- -licenseAqualityNot gradedmaintenanceEnables users to access Naver Maps API functionality including directions, place search, geocoding, and reverse geocoding through a Model Context Protocol server.4
- FlicenseAqualityCmaintenanceNaver Search API + Datalab API MCP server with 19 tools for Korean web search and trend analysis.1919
Appeared in Searches
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/yunkee-lee/mcp-naver-maps'
If you have feedback or need assistance with the MCP directory API, please join our Discord server