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 langchain-ai · MCP Server · ★ 248
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is langchainjs-mcp-adapters safe to install? View the security audit →
LangChain.js MCP Adapters [!IMPORTANT] This package has been migrated into the LangChainJS monorepo. This library provides a lightweight wrapper to allow Model Context Protocol (MCP) services to be used with LangChain.js. This project has moved. For a current description of this project, please see the up-to-date README at the project's new location.
| Stars | 248 |
| Forks | 36 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 48.9315250659798/100 |
| Last Updated | 2025-05-16 |
| Created | 2025-03-03 |
| Platforms | mcp, node |
| Est. Tokens | ~159k |
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langchainjs-mcp-adapters is ** THIS REPO HAS MOVED TO https://github.com/langchain-ai/langchainjs/tree/main/libs/langchain-mcp-adapters ** Adapters for integrating Model Context Protocol (MCP) tools with LangChain.js application. It is categorized as a MCP Server with 248 GitHub stars.
langchainjs-mcp-adapters is primarily written in TypeScript. It covers topics such as agent-tools, ai-tools, javascript.
You can find installation instructions and usage details in the langchainjs-mcp-adapters GitHub repository at github.com/langchain-ai/langchainjs-mcp-adapters. The project has 248 stars and 36 forks, indicating an active community.
langchainjs-mcp-adapters is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to langchainjs-mcp-adapters on Agent Skills Hub include mcp-nixos, drift, llm-functions. 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: