NepseAPI-Unofficial — security grade SAFE, quality 70/100

Security audit verdict: SAFE · quality 70/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by surajrimal07 · MCP Server · ★ 61

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is NepseAPI-Unofficial safe to install? View the security audit →

About NepseAPI-Unofficial

NEPSE API An unofficial API service for Nepal Stock Exchange (NEPSE) that provides real-time market data through REST, WebSocket, and Model Context Protocol (MCP) endpoints. ⚠️ VERY IMPORTANT: Legal & Liability Disclaimer This project is provided "AS IS" without any warranty of any kind, express or implied. By using this software or its hosted services, you are agreeing to accept all risks and responsibilities. Strictly for Educational & Non-Commercial Use This project and its associated services are intended strictly for educational, research, and personal, non-commercial purposes only. Commercial use is strictly prohibited. You may not use this software, its data, or its services to build commercial applications, for financial gain, or in any production trading system. For any commercial use of NEPSE data, you must obtain a license from the Nepal Stock Exchange or an authorized data provider. No Guarantee of Accuracy or Reliability The data is sourced from unofficial channels. The author does not guarantee the accuracy, completeness, timeliness, or reliability of any data provided. Do not

financial-marketsmcpmcp-serversnepalnepal-stock-exchangenepsenepse-apinepse-mcp-serversstock-market

Quick Facts

Stars61
Forks27
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score70.0360205979451/100
Open Issues1
Last Updated2026-09-16
Created2024-04-15
Platformsbrowser, claude-code, mcp, python
Est. Tokens~20k

Compatible Skills

These tools work well together with NepseAPI-Unofficial for enhanced workflows:

  • vn_stock_advisor — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (54%)

NepseAPI-Unofficial alternative? Top 6 similar tools

Looking for a NepseAPI-Unofficial alternative? If you're comparing NepseAPI-Unofficial with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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    Absurdly easy Model Context Protocol Servers in Typescript

  • magg by sitbon · ⭐ 142

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  • Financial-Modeling-Prep-MCP-Server by imbenrabi · ⭐ 140

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Frequently Asked Questions

What is NepseAPI-Unofficial?

NepseAPI-Unofficial is Unlock Nepal Stock Exchange (NEPSE) data with this powerful unofficial API. Features REST, WebSocket, and a first-of-its-kind Model Context Protocol (MCP) server, enabling AI models like Claude to per. It is categorized as a MCP Server with 61 GitHub stars.

What programming language is NepseAPI-Unofficial written in?

NepseAPI-Unofficial is primarily written in Python. It covers topics such as financial-markets, mcp, mcp-servers.

How do I install or use NepseAPI-Unofficial?

You can find installation instructions and usage details in the NepseAPI-Unofficial GitHub repository at github.com/surajrimal07/NepseAPI-Unofficial. The project has 61 stars and 27 forks, indicating an active community.

What license does NepseAPI-Unofficial use?

NepseAPI-Unofficial is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to NepseAPI-Unofficial?

The top alternatives to NepseAPI-Unofficial on Agent Skills Hub include model-context-protocol-resources, gram, mcp-fusion. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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