DART 재무제표 분석 MCP 서버
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 |
|---|---|
| get_company_listC | 분석 가능한 회사 목록을 가져옵니다 |
| analyze_financial_dataC | 다중 기업의 재무제표 데이터를 분석하고 시각화합니다 |
| generate_financial_chartC | 특정 재무 지표에 대한 텍스트 차트를 생성합니다 |
| generate_financial_dashboardC | 종합적인 재무 분석 대시보드를 생성합니다 |
| generate_html_dashboardC | HTML 형식의 재무 분석 대시보드를 생성합니다 |
| generate_comparison_tableC | 기업별 재무 지표 비교표를 생성합니다 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
There is significant overlap in purpose between tools like generate_financial_chart, generate_financial_dashboard, and generate_html_dashboard, all focused on visualization outputs. However, analyze_financial_data and get_company_list have clearer distinct roles in analysis and data retrieval, preventing complete confusion.
All tool names follow a consistent verb_noun pattern using snake_case, such as analyze_financial_data, generate_comparison_table, and get_company_list. This predictability makes the set easy to navigate and understand at a glance.
With 6 tools, this server is well-scoped for financial statement analysis, covering key operations like data analysis, visualization, and company listing. Each tool appears to serve a specific function without unnecessary bloat or missing essentials.
The tool set covers analysis and visualization well but lacks obvious CRUD operations for financial data, such as fetching raw financial statements or updating data. This gap might limit agents in performing comprehensive financial workflows beyond the provided tools.