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li-evan

A-Share Multi-Dimensional Quantitative Analysis

by Evan · GitHub ↗ · v1.5.0 · MIT-0
cross-platform ⚠ suspicious
457
Downloads
0
Stars
2
Active Installs
6
Versions
Install in OpenClaw
/install yanpan-finance
Description
A-Share Multi-Dimensional Quantitative Analysis MCP Server - broker research reports, AI news analysis, and stock comprehensive analysis
Usage Guidance
This package is inconsistent: the SKILL.md points clients at an external MCP endpoint (42.121.167.42) and expects you to get an API key via WeChat, but the bundle also contains runnable server code with embedded MongoDB credentials and different IPs. Before installing or running anything: 1) Do not run server.py unless you trust the source—running it will connect to a remote MongoDB (hard-coded creds) and open a public HTTP service. 2) Verify the ownership and legitimacy of the advertised endpoint (42.121.167.42) and the MongoDB host (121.43.242.239) — ask the provider for official documentation, who operates those hosts, and why credentials are embedded. 3) Avoid sending your platform credentials or secrets to the WeChat contact; request platform-managed API keys or an official API page. 4) If you only intend to call the remote MCP endpoint, treat it like any external API: review privacy, data retention, and what data you will send. 5) If you need to run or modify the server code, remove hard-coded secrets, rotate any exposed credentials, and host the service in a controlled environment. Given the embedded plaintext credentials and endpoint mismatches, proceed with caution or choose a more transparent provider.
Capability Analysis
Type: OpenClaw Skill Name: yanpan-finance Version: 1.5.0 The skill provides financial analysis tools by connecting to a remote MongoDB instance (121.43.242.239) and references a hosted MCP server (42.121.167.42). While the code aligns with its stated purpose of A-share market analysis, server.py contains hardcoded database credentials ('tradingagents123') and a default API token ('yanpan-mcp-secret-2026'), which are significant security vulnerabilities. These risks appear to be unintentional design flaws for ease-of-use rather than intentional malice.
Capability Assessment
Purpose & Capability
The listed tools (research report search, news analysis, stock analysis) match the server.py implementation: it queries MongoDB collections and returns report-like content. However, SKILL.md tells clients to connect to an external MCP endpoint (http://42.121.167.42:9800/mcp) while the included server runs on 0.0.0.0:9800 and embeds a different remote MongoDB host (121.43.242.239). The presence of runnable server code is not strictly necessary for a client-only instruction skill and the mismatched IPs and embedded DB usage reduce coherence.
Instruction Scope
SKILL.md itself is narrow: it instructs adding an MCP server entry pointing to an external URL and obtaining an API key via WeChat. It does not instruct reading local files or other system state. However, the distributed artifact includes server.py which, if executed, will open a public HTTP server, verify a static token, and connect to a remote MongoDB. That behavior is outside what the SKILL.md asks a user to do and expands scope if a user chooses to run the code.
Install Mechanism
There is no install spec (instruction-only), so nothing is automatically downloaded or installed by the platform. The project includes a pyproject declaring dependencies (mcp, pymongo, uvicorn) which are reasonable for a Python MCP server. Risk arises only if the user manually installs or runs the included code.
Credentials
The skill metadata declares no required environment variables, but server.py expects and uses environment variables (API_TOKEN, MONGODB_HOST/PORT/USERNAME/PASSWORD/AUTH_SOURCE). Worse, the file contains default plaintext MongoDB credentials and host/IP (username: 'admin', password: 'tradingagents123', host: 121.43.242.239) and a default API_TOKEN. Embedding remote DB credentials in the bundle is disproportionate to a client-side integration and could expose or encourage use of a remote database with unclear ownership. Additionally, SKILL.md asks users to contact a WeChat ID for an API key rather than providing platform-managed credentials.
Persistence & Privilege
The skill does not request always:true and is user-invocable only. There is no evidence it modifies other skills or system settings. However, if someone runs the included server.py, it will bind to 0.0.0.0:9800 and serve data authenticated by a static token—this creates a persistent network service outside the skill registry and can expose data depending on how it's configured.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install yanpan-finance
  3. After installation, invoke the skill by name or use /yanpan-finance
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.5.0
Update WeChat contact to ptcg12345
v1.4.0
Replace API token with placeholder
v1.3.0
Rename to A-Share Multi-Dimensional Quantitative Analysis; add WeChat contact (wolfking) for API key
v1.2.0
Remove hardcoded token, use YANPAN_API_KEY env variable
v1.1.0
Hosted service mode - connect directly, no deployment needed
v1.0.0
Initial release: 券商研报搜索、新闻分析、股票综合分析 MCP Server
Metadata
Slug yanpan-finance
Version 1.5.0
License MIT-0
All-time Installs 2
Active Installs 2
Total Versions 6
Frequently Asked Questions

What is A-Share Multi-Dimensional Quantitative Analysis?

A-Share Multi-Dimensional Quantitative Analysis MCP Server - broker research reports, AI news analysis, and stock comprehensive analysis. It is an AI Agent Skill for Claude Code / OpenClaw, with 457 downloads so far.

How do I install A-Share Multi-Dimensional Quantitative Analysis?

Run "/install yanpan-finance" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is A-Share Multi-Dimensional Quantitative Analysis free?

Yes, A-Share Multi-Dimensional Quantitative Analysis is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does A-Share Multi-Dimensional Quantitative Analysis support?

A-Share Multi-Dimensional Quantitative Analysis is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created A-Share Multi-Dimensional Quantitative Analysis?

It is built and maintained by Evan (@li-evan); the current version is v1.5.0.

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