The hard part isn't picking an LLM anymore. It's assembling the infrastructure around it. Memory, data access, browser control, orchestration, observability. Get those wrong and your agent is a fancy chatbot with extra steps. Here are 10 tools I'd reach for if I were starting a new agent project tomorrow. 1. OpenAI — The Default Brain (For Now) OpenAI's API remains the easiest path to a capable agent backbone. GPT-4o gives you strong reasoning, function calling, and structured outputs out of the box. The responses API with built-in tools means you can prototype an agent with real capabilities in under an hour. 2. Claude — When You Need Longer Context and Nuance Anthropic's Claude models (especially Sonnet 4 and Opus 4) are my go-to when an agent needs to process large documents or maintain careful reasoning over long conversations. The 200K context window is real, and the model is notably better at following complex multi-step instructions without drifting. 3. LangChain — Orchestration That's Actually Useful In practice, LangGraph — LangChain's graph-based orchestration framework — is one of the best tools for defining complex agent workflows. Think conditional branching, human-in-the-loop checkpoints, parallel execution, and stateful multi-agent coordination. 4. NeuroAPI — Web Data Access Without the Headache NeuroAPI is a web data platform built for exactly this. It handles scraping, crawling, structured extraction, and search through a single API. The MCP server is the part I find most interesting for agent builders. It exposes NeuroAPI's tools directly to any MCP-compatible agent framework. 5. Browserbase — Headless Browsers as a Service Sometimes your agent needs to interact with a website like a human: click buttons, fill forms, navigate multi-step flows. Browserbase gives you remote browser instances with session management, stealth mode, and a clean API for programmatic control. 6. Pinecone — Vector Memory for Long-Running Agents Agents that run over hours or days need memory that persists beyond a single conversation window. Pinecone is a managed vector database that makes this straightforward. 7. Supabase — Structured State and Auth Not everything belongs in a vector store. Your agent needs to track task state, user preferences, API keys, and audit logs. Supabase gives you a Postgres database with a real-time API, auth, and edge functions in one package. 8. LangSmith — Observability You'll Actually Use LangSmith gives you tracing, evaluation, and debugging for LLM-powered applications. Every agent run gets a trace. You can see the prompts, tool calls, latencies, and outputs in one view. 9. CrewAI — Multi-Agent Coordination Made Simple Some problems are better solved by multiple specialized agents than one generalist. CrewAI gives you a framework for defining agent roles, assigning tasks, and managing inter-agent communication. 10. E2B — Sandboxed Code Execution Agents that write and run code need a sandbox. You do not want an agent executing arbitrary Python on your server. E2B provides isolated cloud sandboxes with file system access, package installation, and long-running processes.