Fund MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| PORT | No | Port number for the server | 3000 |
| NODE_ENV | No | Node environment | production |
| LLM_API_KEY | No | Your LLM API key | |
| LLM_API_URL | No | Your LLM API URL |
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 |
|---|---|
| fund.echoC | Echo back a message. Example interface for scaffold. |
| fund.knoewledgeC | 获取的知识库列表信息 |
| fund.stock_searchC | 搜索股票信息，基于东方财富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 3 tools
The three tools have clearly distinct purposes: echo is for testing/echoing messages, knowledge is for retrieving knowledge base information, and stock_search is for searching stock data. There is no overlap in functionality, making it easy for an agent to select the correct tool.
All tools follow a consistent naming pattern: 'fund.' prefix followed by a descriptive term (echo, knowledge, stock_search). The terms are in snake_case and clearly indicate the tool's function, with no deviations or mixed conventions.
With only 3 tools, the server feels thin for a 'Fund MCP Server' that implies financial or investment functionality. While the tools cover basic operations (testing, knowledge retrieval, stock search), the scope suggests more comprehensive tools (e.g., for portfolio management, analysis) might be missing, making it borderline appropriate.
The tool surface is significantly incomplete for a fund-related domain. It lacks core operations such as creating/updating/deleting fund data, analyzing investments, or managing portfolios. The tools provided (echo, knowledge list, stock search) are limited and do not support typical fund management workflows, leading to potential agent failures.