Naver Finance Crawl MCP
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| crawl_top_stocksA | Crawl top searched stocks from Naver Finance. Returns a list of the most searched stocks with their codes, names, current prices, and change rates. |
| crawl_stock_detailA | Crawl detailed information for a specific stock by its 6-digit code. Returns comprehensive data including company info, stock prices, trading volume, and financial metrics. |
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 2 tools
The two tools have clearly distinct purposes: crawl_stock_detail focuses on retrieving detailed information for a specific stock by its code, while crawl_top_stocks retrieves a list of top searched stocks. There is no overlap or ambiguity between these functions, making it easy for an agent to select the appropriate tool.
Both tool names follow a consistent verb_noun pattern with 'crawl_' as the prefix, followed by descriptive nouns (stock_detail and top_stocks). This uniformity enhances readability and predictability, adhering to a clear naming convention throughout the set.
With only 2 tools, the server feels thin for a finance crawling domain, as it lacks operations for broader data retrieval, such as market indices, sector analysis, or historical data. While the tools are well-defined, the limited count may restrict agent capabilities in handling more complex financial queries.
The tool set is significantly incomplete for a finance crawling server. It covers specific stock details and top searches but misses essential operations like crawling market summaries, financial news, historical price data, or sector performance. These gaps will likely cause agent failures when broader financial information is needed.