MCP File Server
MCP 파일 서버
표준화된 인터페이스를 통해 파일 시스템 작업을 제공하는 MCP(모델 컨텍스트 프로토콜) 서버 구현입니다.
개요
MCP 파일 서버는 AI 모델이 표준화된 API를 통해 로컬 파일 시스템에서 파일 작업을 수행할 수 있도록 지원합니다. MCP 파일 서버는 Model Context Protocol SDK를 사용하여 구축되었으며, 파일을 읽고, 생성하고, 나열하는 도구를 제공합니다.
Related MCP server: filesystem-mcp-server
특징
파일 생성 : 지정된 내용으로 새 파일을 생성합니다.
파일 읽기 : 기존 파일의 내용을 읽습니다.
디렉토리 내용 나열 : 자세한 정보와 함께 파일 및 디렉토리 나열
성능 모니터링 : 오류 추적 및 성능 모니터링을 위한 Sentry 통합 기능 내장
설치
지엑스피1
용법
MCP 파일 서버를 시작합니다.
node src/index.js서버는 MCP 프로토콜을 사용하여 stdin/stdout을 통해 통신합니다.
사용 가능한 도구
createfile
제공된 콘텐츠로 지정된 경로에 새 파일을 만듭니다.
매개변수:
filePath: 파일이 생성되어야 하는 경로content: 파일에 쓸 내용
보고:
파일 경로 및 크기 정보가 포함된 성공 메시지
읽기 파일
지정된 경로에 있는 파일의 내용을 읽습니다.
매개변수:
filePath: 읽을 파일의 경로
보고:
파일의 내용
목록 파일
지정된 경로에 있는 파일과 디렉토리를 나열합니다.
매개변수:
path: 내용을 나열할 디렉토리 경로
보고:
파일 이름, 크기, 유형을 포함하는 마크다운 테이블
환경 변수
SENTRY_DSN: 오류 추적을 위한 Sentry 데이터 소스 이름(선택 사항)
종속성
@modelcontextprotocol/sdk: MCP SDK 패키지zod: 스키마 검증@sentry/node: 오류 추적 및 성능 모니터링
예시
MCP 프로토콜을 통해 이러한 도구를 호출하는 방법의 예:
{
"name": "createfile",
"params": {
"filePath": "example/test.txt",
"content": "Hello, world!"
}
}{
"name": "readfile",
"params": {
"filePath": "example/test.txt"
}
}{
"name": "listfiles",
"params": {
"path": "example"
}
}Available Tools
3 toolscreatefileD
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Content to write to the file | |
| filePath | Yes | Path where the file should be created |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no 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?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listfilesD
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no 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?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
readfileD
| Name | Required | Description | Default |
|---|---|---|---|
| filePath | Yes | Path to the file to read |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no 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?
Tool has no description.
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?
Tool has no description.
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.
3 tool updates
v1.0.0- First observed
createfile - First observed
listfiles - First observed
readfile
TDQS
Scored across 3 tools
The three tools have clearly distinct purposes: createfile for creating files, listfiles for listing files, and readfile for reading files. There is no overlap or ambiguity between these operations, making it easy for an agent to select the right tool for each task.
All tool names follow a consistent verb_noun pattern (createfile, listfiles, readfile) with no deviations. The naming is uniform and predictable, using lowercase letters and clear action-object combinations throughout.
With only three tools, the server feels thin for a file management domain, as it lacks essential operations like update, delete, or write to files. While the count is minimal, it covers basic CRUD aspects but leaves notable gaps in functionality.
The tool set is significantly incomplete for file management, missing critical operations such as updatefile, deletefile, and writefile. This creates dead ends for agents trying to perform common file workflows, leading to potential failures in tasks requiring modification or deletion.
Maintenance
Related MCP Connectors
Securely search and manage workspace context files for AI agents and teams.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
A Model Context Protocol server for Wix AI tools
Browse and manage files in your Moxt AI workspace from any MCP client.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceA Model Context Protocol (MCP) server that allows AI models to safely access and interact with local file systems, enabling reading file contents, listing directories, and retrieving file metadata.13 npm10MIT
- AlicenseAqualityFmaintenanceA Model Context Protocol server that provides AI agents with secure access to local filesystem operations, enabling reading, writing, and managing files through a standardized interface.1078 npm53Apache 2.0
- FlicenseNot gradedqualityDmaintenanceEnables LLMs to securely read, search, and analyze local file systems through the Model Context Protocol. Provides tools for listing files, pattern-based searching, and reading file contents with built-in security validation.6-
- FlicenseNot gradedqualityDmaintenanceEnables AI models to securely read, write, and query metadata of local files through a controlled file system interface, with support for local and Azure deployment.-
Appeared in Searches
- Tools to Enhance Cursor AI Performance
- MCP servers to enhance agent-based medical project performance
- How to organize or locate my project file
- Developing and redeveloping web frontend and Python backend projects, including frontend-backend integration and debugging
- A system or tool for reading, writing, and interacting with local storage