by teddynote-lab · MCP Server · ★ 690
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🔒 Is langgraph-mcp-agents safe to install? View the security audit →
LangGraph Agents + MCP Project Overview is a toolkit provided by LangChain AI that enables AI agents to interact with external tools and data sources through the Model Context Protocol (MCP). This project provides a user-friendly interface for deploying ReAct agents that can access various data sources and APIs through MCP tools. Features Streamlit Interface: A user-friendly web interface for interacting with LangGraph with MCP tools Tool Management: Add, remove, and configure MCP tools through the UI (Smithery JSON format supported). This is done dynamically without restarting the application Streaming Responses: View agent responses and tool calls in real-time Conversation History: Trac
git clone https://github.com/teddynote-lab/langgraph-mcp-agents.gitTaken from the project's README on GitHub. Check the security audit before running it.
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 →
| Stars | 690 |
| Forks | 232 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 73.6630565599681/100 |
| Open Issues | 4 |
| Last Updated | 2025-04-14 |
| Created | 2025-03-30 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~162k |
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langgraph-mcp-agents is LangGraph-powered ReAct agent with Model Context Protocol (MCP) integration. A Streamlit web interface for dynamically configuring, deploying, and interacting with AI agents capable of accessing vario. It is categorized as a MCP Server with 690 GitHub stars.
langgraph-mcp-agents is primarily written in Python.
The README on GitHub (github.com/teddynote-lab/langgraph-mcp-agents) gives: git clone https://github.com/teddynote-lab/langgraph-mcp-agents.git. Usage details are in the same README.
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: