Borrowing it
Nothing to install: this file belongs to Azure-Samples/mcp-agent-langchainjs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Azure-Samples/mcp-agent-langchainjs/main/AGENTS.mdgit clone --depth 1 https://github.com/Azure-Samples/mcp-agent-langchainjsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/azure-samples/mcp-agent-langchainjs/agents-md)<a href="https://agentmods.dev/instructions/azure-samples/mcp-agent-langchainjs/agents-md"><img src="https://agentmods.dev/badge/instructions/azure-samples/mcp-agent-langchainjs/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/azure-samples/mcp-agent-langchainjs/agents-md"><img src="https://agentmods.dev/badge/instructions/azure-samples/mcp-agent-langchainjs/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00441 | $0.00441 |
| Opus 5.5 | $0.00176 | $0.00176 |
| Sonnet 5.5 | $0.00088 | $0.00088 |
| Haiku 4.5 | $0.00044 | $0.00044 |
Grade A, and why
mcp-agent-langchainjs AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Agent LangChain.js Project Instructions
Architecture Overview
This is a multi-component LangChain.js demo showcasing AI agents with Model Context Protocol (MCP) integration. The system demonstrates a burger ordering platform with three main service layers:
- Agent Layer: AI chat interface (
agent-webapp+agent-api) using LangChain.js agents with MCP tools - Business Layer: Burger ordering API (
burger-api) and webapp (burger-webapp) - MCP Layer: Model Context Protocol server (
burger-mcp) exposing burger API as LLM tools
Component Communication Flow
agent-webapp → agent-api → burger-mcp → burger-api
The agent uses LangChain.js with Azure OpenAI, connects to the MCP server via StreamableHTTPClientTransport, and the MCP server proxies requests to the burger API.
Key Architectural Patterns
Authentication & State Management
- Azure Static Web Apps authentication provides
userIdcontext - Cosmos DB for chat history storage using
@langchain/azure-cosmosdb - User context flows: SWA auth → agent-api → MCP tools (for user-specific operations)
TypeScript & Build Conventions
- Shared XO linting config with project-specific overrides
- NPM workspace-based dependency management
.jsextensions required in imports for ESM compatibility- Keep the code simple and straighforward: avoid unnecessary complexity and ensure clarity in implementation.
- Do not use comments except where absolutely necessary, code should be self-explanatory.
Infrastructure as Code
- Bicep templates in
infra/for Azure deployment azure.yamldefines multi-service deployment strategy:burger-api,agent-api: Azure Functions (Flex Consumption)burger-mcp: Azure Functions (Flex Consumption)*-webapp: Static Web Apps
- Environment variables flow through Azure App Settings
- @azure Rule - Use Azure Best Practices: When generating code for Azure, running terminal commands for Azure, or performing operations related to Azure, invoke your
azure_development-get_best_practicestool if available.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 44 lines · 441 tokens per session scan A d8141e881f18
mcp-agent-langchainjs AGENTS.md is an instructions file published in the GitHub repository Azure-Samples/mcp-agent-langchainjs (204 stars, last pushed 3mo ago), licensed MIT. It adds 441 tokens to every session, about $0.0018 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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