Multi-Purpose MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| HF_TOKEN | No | Your Hugging Face API token for image generation functionality |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| greetingB | 사용자의 이름과 언어를 입력받아 해당 언어로 인사하는 도구 |
| calculatorC | 두 숫자에 대한 사칙연산을 수행하는 계산기 도구 |
| current_timeA | 현재 시간을 지정된 시간대에서 조회하는 도구. 시간대를 입력하지 않으면 한국 시간대(Asia/Seoul)를 사용합니다. |
| code_reviewC | 사용자가 제공한 코드에 대한 상세한 코드 리뷰 프롬프트를 생성하는 도구 |
| generate_imageC | 텍스트 프롬프트를 사용하여 이미지를 생성하는 도구 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| 서버 정보 | 현재 MCP 서버의 정보를 반환합니다 |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose with no overlap: calculator for arithmetic, code_review for code analysis, current_time for time retrieval, generate_image for image generation, and greeting for personalized salutations. The descriptions clearly differentiate their domains, making misselection unlikely.
All tool names follow a consistent snake_case pattern with descriptive noun-based naming (e.g., calculator, code_review, current_time). There are no deviations in style or verb usage, making the set predictable and easy to parse.
With 5 tools, the count is reasonable but feels thin for a 'Multi-Purpose' server, as it covers only a few unrelated domains without depth in any one area. It's borderline for the stated scope, lacking the breadth implied by the server name.
The server claims to be multi-purpose but has significant gaps: tools are isolated with no clear domain coverage (e.g., no CRUD operations, limited utility functions), and the set doesn't support cohesive workflows. This will likely cause agent failures when trying to accomplish broader tasks.