Search Stock News MCP Server
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 |
|---|---|
| search-stock-newsC | Search for stock-related news using Tavily API |
| general-searchC | Perform a general web search using Tavily API |
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: 'general-search' is for broad web searches, while 'search-stock-news' is specifically for stock-related news. There is no overlap or ambiguity between them, making it easy for an agent to select the appropriate tool based on the query context.
Both tool names follow a consistent verb_noun pattern with hyphens: 'general-search' and 'search-stock-news'. They use the same naming convention throughout, making the set predictable and readable without any deviations or mixed styles.
With only two tools, the server feels under-scoped for a 'Search Stock News MCP Server'. While the tools cover general and stock-specific searches, the domain suggests potential for more operations like filtering, sorting, or retrieving detailed news, making the count too low for the apparent purpose.
The tool surface is significantly incomplete for a stock news server. It lacks essential operations such as filtering news by date, source, or stock ticker, retrieving trending news, or accessing detailed article content. This will likely cause agent failures when trying to perform comprehensive stock news analysis.