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 Azure-Samples · MCP Server · ★ 194
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-agent-langchainjs safe to install? View the security audit →
AI Agent with MCP tools using LangChain.js ⭐ If you like this sample, star it on GitHub — it helps a lot! [Overview](
| Stars | 194 |
| Forks | 94 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 70.4197119915497/100 |
| Last Updated | 2026-07-08 |
| Created | 2025-07-07 |
| Platforms | mcp, node |
| Est. Tokens | ~18k |
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mcp-agent-langchainjs is Serverless AI agent using LangChain.js and Model Context Protocol (MCP) integration to order burgers from a burger restaurant. It is categorized as a MCP Server with 194 GitHub stars.
mcp-agent-langchainjs is primarily written in TypeScript. It covers topics such as agent, ai, api.
You can find installation instructions and usage details in the mcp-agent-langchainjs GitHub repository at github.com/Azure-Samples/mcp-agent-langchainjs. The project has 194 stars and 94 forks, indicating an active community.
mcp-agent-langchainjs is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcp-agent-langchainjs on Agent Skills Hub include after-effects-mcp, octocode-mcp, context-space. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: