Memory Store MCP Server
메모리 저장소 MCP 서버
Puppeteer를 사용하여 웹 검색 기능을 제공하는 MCP(Model Context Protocol) 서버입니다.
특징
Google을 통한 웹 검색 기능
구조화된 JSON 결과
가볍고 무국적 디자인
MCP 지원 시스템과의 쉬운 통합
Related MCP server: webmcp
설치
저장소를 복제합니다.
지엑스피1
종속성 설치:
npm install프로젝트를 빌드하세요:
npm run build
구성
다음 환경 변수를 사용하여 프로젝트 루트에 .env 파일을 만듭니다.
# Puppeteer configuration
PUPPETEER_EXECUTABLE_PATH=/path/to/chrome
PUPPETEER_HEADLESS=true
# Server settings
PORT=3000용법
서버를 시작합니다:
npm startMCP 클라이언트에서 서버를 사용할 수 있습니다. MCP를 통한 사용 예:
{
"tool": "search_web",
"arguments": {
"query": "example search"
}
}개발
프로젝트 구축
npm run build테스트 실행
npm test린팅
npm run lint서식
npm run format특허
이 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다. 자세한 내용은 라이선스 파일을 참조하세요.
Available Tools
1 toolsearch_webC
Search the web using Google
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query |
TDQS
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 states the basic function without mentioning rate limits, authentication needs, result format, pagination, or any other operational characteristics that would help an agent understand how to interact with it effectively.
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 extremely concise at just four words, front-loaded with the core function, and contains no unnecessary information. Every word earns its place in communicating the essential purpose.
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 insufficiently complete. It doesn't explain what kind of results to expect, how they're structured, or any behavioral aspects like limitations or error handling, leaving significant gaps for agent understanding.
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 schema description coverage is 100%, so the input schema already documents the single 'query' parameter adequately. The description doesn't add any additional meaning or context about the parameter beyond what's in the schema, which meets the baseline for high schema coverage.
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 ('Search') and target ('the web using Google'), providing a specific verb+resource combination. However, with no sibling tools mentioned, there's no opportunity to distinguish from alternatives, which prevents a perfect score.
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 other search methods or tools, nor does it mention any prerequisites or exclusions. It simply states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
search_web
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'search_web' has a single, distinct purpose that cannot be confused with any other tool in this set.
The single tool name follows a clear verb_noun pattern ('search_web'), and since there is only one tool, consistency is inherently perfect with no deviations or mixed conventions to evaluate.
A single tool is too few for a server named 'Memory Store MCP Server', which implies functionality related to storing, retrieving, or managing memory data. The tool 'search_web' does not align with this domain, making the count inappropriate and mismatched with the apparent scope.
The tool set is severely incomplete for the inferred domain of memory storage. There are no tools for creating, reading, updating, or deleting memory entries, which are essential operations for a memory store, leaving significant gaps that will cause agent failures.
Maintenance
Related MCP Connectors
MCP server for Google search results via SERP API
MCP server for Firecrawl — web search, scraping, and biomedical/arXiv paper search.
Free web search for AI agents. No API key required. Hosted MCP in active development.
Docs: https://docs.keenable.ai/mcp-server Keenable is a free, remote MCP server that gives agents access to the web index. Search the web with ranked results and date/site filters, then fetch any indexed page as clean markdown. Works out of the box with no account or API key.
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