Arcade is the MCP runtime for secure agent authorization, reliable tools, and governance. Ship multi-user AI agents faster and scale with control.
The runtime layer from Arcade makes MCP enterprise-ready. Connects to identity providers, enforces agent authorization, and enables real actions in Google, Slack, and Salesforce. Arcade is the best platform to facilitate secure and interactive MCP Integrating with Arcade’s MCP runtime has been remarkably easy, so we can focus on delivering personalized coaching experiences. Plus, the composability across LLM architectures gives us the architectural freedom to scale, accelerating our product development without compromising quality or flexibility. By using Arcade, we’re able to authenticate users’ Twitter/LinkedIn accounts without worrying about refresh tokens, broken auth, or any of the other hassle that comes with setting up auth connections. Arcade nails the sweet spot between AI, auth, and developer experience. We’re using it and it’s insanely useful - finally a product that lets AI agents actually do stuff. We built an AI sales agent that knows everything about every deal by analyzing calls, emails, and CRM data. With Arcade, that agent can now go the extra mile and effortlessly take secure actions on behalf of a rap - turning a smart assistant into a revenue-driving powerhouse. With Arcade, we can bypass the complexity of Google service integration and fast-forward our AI development to building tools for our AI Assistant that teachers can actually use. Arcade is the MCP runtime that makes AI agents production-ready. Deploy multi-user agents that take actions across any business system with controlled user-specific permissions—no complex infrastructure required. From pilots to enterprise-wide deployments, Arcade handles authorization, reliability, and governance so your teams can focus on building agents at scale. Ship multi-user agents that take actions across any system, with security and control built in Deploy agents even your security team will love. Agents act with user-specific permissions—not service accounts—and integrate with your existing OAuth and IDP flows. No more token headaches - just pure magic. Access the largest catalog of high-quality MCP tools—not just API wrappers. Built for agents from the ground up to deliver better reliability and lower costs at scale. Ship more complex agents faster with tools that actually work. Easily build custom tools with the same open source framework we use internally. OAuth and evals built-in. Designed to integrate with the runtime so you can securely scale to production. Complete visibility and control over every tool and agent in your organization. Your team ships faster, stays compliant, and scales without the chaos. Deploy in the cloud, your VPC, on-premises, or fully air-gapped. You control where your data lives and how it's secured. From Concept to Production in Minutes
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Pricing found: $25 /month, $0.05, $0.01, $0.50, $0.05
Built a WhatsApp AI assistant with Claude Code as an OpenClaw alternative
As a startup founder, I'm always looking for ways to improve my productivity. The promise of OpenClaw is enticing, however I couldn't get past the security model, or lack thereof. I was already using Claude Code heavily and am a heavy WhatsApp user, so I wanted something that brings both together: WhatsApp for messaging my AI assistant and Claude Code as the agentic brain. The benefit of using Claude Code: I'm already paying for a Claude Max subscription, so this covers the cost. Not to mention the fact I trust Anthropic's runtime more. The stack is a local relay server for WhatsApp webhooks, an MCP server bridging to Claude Code, and Arcade for scoped auth to Google Calendar, Gmail, and Slack. Here is the full working code https://github.com/manveer/whatsapp-assistant submitted by /u/manveerc [link] [comments]
View originalI am doing a multi-model graph database in pure Rust with Cypher, SQL, Gremlin, and native GNN looking for extreme speed and performance
Hi guys, I'm a PhD student in Applied AI and I've been building an embeddable graph database engine from scratch in Rust. I'd love feedback from people who actually work with graph databases daily. I got frustrated with the tradeoffs: Neo4j is mature but JVM-heavy and single-model. ArcadeDB is multi-model but slow on graph algorithms. Vector databases like Milvus handle embeddings but have zero graph awareness. I wanted one engine that does all three natively. So I would like if someone could give me feedback or points to improve it, I am very open mind for whatever opinion I was working several months with my university professors and I decided to publish the code yesterday night because I guessed its more or less reddit to try it. The repo is: https://github.com/DioCrafts/BikoDB Guys, as I told you, whatever feedback is more than welcome. PD: Obviously is open source project. Cheers! submitted by /u/torrefacto [link] [comments]
View originalClaude Code session dashboard - open source, 3 commands to install
I've been running 3–4 Claude Code sessions simultaneously and kept hitting the same problem: no combined cost view, no way to see which session is thinking vs idle vs waiting for input, no visibility into context window usage across sessions. So I built this: https://github.com/Stargx/claude-code-dashboard How Claude helped build it: The entire project was written using Claude Code. I described the problem, and Claude figured out that Claude Code writes JSONL session logs to ~/.claude/projects/ — then built the file watcher, the Express API, and the frontend in a single HTML file. I basically directed it and it did the heavy lifting. Felt very meta: using Claude Code to build a tool for watching Claude Code. What it shows per session: - Token usage and cost (with correct per-model pricing) - Status — thinking / waiting / idle / stale - Context window usage as a visual progress bar - Active subagents while they're running - Which files the session is currently working on - Expandable activity log - Git branch and permission mode (AUTO-EDIT / YOLO) How it works: Claude Code writes JSONL session logs to `~/.claude/projects/`. The dashboard watches those files and renders everything in a browser tab. No WebSockets, no build step, no cloud — just Node.js tailing local files and a single HTML file for the UI. Quick start: ``` git clone https://github.com/Stargx/claude-code-dashboard cd claude-code-dashboard npm install && npm start ``` Then open http://localhost:3001. Free and MIT licensed. Would love feedback — especially if you're on macOS or Linux and hit any issues with session detection. submitted by /u/ColdBeamGames [link] [comments]
View originalRepository Audit Available
Deep analysis of ArcadeAI/arcade-ai — architecture, costs, security, dependencies & more
Yes, Arcade AI offers a free tier. Pricing found: $25 /month, $0.05, $0.01, $0.50, $0.05
Key features include: Archer Slack Agent, Arcade Chat, How to Build a Telegram Agent for Google Calendar Integration, Build a Google Calendar AI Agent in 60 seconds with Arcade.dev's MCP Servers, Build an AI Agent for Gmail, Your AI Agent Just Got a Credit Card, Alex Salazar, Sam Partee.
Arcade AI has a public GitHub repository with 841 stars.
Based on user reviews and social mentions, the most common pain points are: token usage.
