About ai-agent-mcp-servers
An MCP server project for fintech backend services, intended to support data analysis. Its README notes that stock market data can be fetched from akshare and shows stdio and SSE startup configurations.
Key features
- 01Fintech backend MCP servers
- 02Stock market data via akshare
- 03stdio and SSE startup configurations
Use cases
- 01Analyze fintech data with an AI agent
- 02Fetch stock market data from akshare
MCP support
It provides MCP servers for fintech backend services. The README shows configurations for connecting through stdio or SSE.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEai-agent-mcp-servers
This project provide mcp servers to fintech backend services to support data analysis. The stock market data can be fetched from https://akshare.akfamily.xyz/data/stock/stock.html
How to run
uv --directory /Users/fengshiyi/Downloads/shayne/learning/LLM/my-projects/fintech/ai-agent-mcp-servers/src/financial_mcp_server run ai-agent-mcp-servers
- Claude Desktop or Cline when start the server as stdio
{
"mcpServers": {
"job_hunting_server": {
"command": "uv",
"args": [
"--directory",
"/Users/fengshiyi/Downloads/shayne/learning/LLM/my-projects/fintech/ai-agent-mcp-servers/src/financial_mcp_server",
"run",
"ai-agent-mcp-servers"
]
}
}
}
when start the server as sse
{
"mcpServers": {
"job_hunting_server": {
"command": "uv",
"args": [
"--directory",
"/Users/fengshiyi/Downloads/shayne/learning/LLM/my-projects/fintech/ai-agent-mcp-servers/src/financial_mcp_server",
"run",
"ai-agent-mcp-servers"
]
}
}
}
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.