Practical Multi-Step Agent Setups

15 entries shown

1. 1Model Context Protocol (MCP)

   Tool · Effort: Medium

   Verdict: MCP is the plumbing that makes agents useful: write a tool server once and use it from Claude, Cursor, VS Code and more. Learn it before building custom tool integrations.

2. 2MCP reference servers

   Tool · Effort: Low

   Verdict: Start here before writing your own server: filesystem, git, fetch, memory and more. Also the best code to copy patterns from.

3. 3GitHub MCP Server

   Tool · Effort: Low

   Verdict: The standard way to let an agent read issues, open PRs and inspect CI. Use fine-grained tokens and read-only toolsets where you can.

4. 4browser-use

   Tool · Effort: Medium

   Verdict: A popular way to let an LLM operate websites that have no API. Great for prototyping web tasks; production use needs retries, guardrails and a careful look at site terms.

5. 5Stagehand

   Tool · Effort: Medium

   Verdict: A good middle ground between brittle selectors and fully autonomous browser agents: use code where you can and AI where the page is unpredictable. Strong choice for TypeScript teams.

6. 6LangGraph

   Tool · Effort: High

   Verdict: Use it when you need explicit control: branching, retries, human-in-the-loop and durable state. More code than higher-level frameworks, but far more predictable in production.

7. 7CrewAI

   Tool · Effort: Medium

   Verdict: Fast to get a role-based multi-agent setup running (researcher, writer, reviewer). Good for content and research pipelines. Watch for over-engineering: one agent is often enough.

8. 8OpenAI Agents SDK

   Tool · Effort: Medium

   Verdict: Minimal and easy to learn: agents, tools, handoffs, guardrails and tracing. A good default if you want something lighter than LangGraph.

9. 9Claude Agent SDK

   Tool · Effort: Medium

   Verdict: If Claude Code already works for you, this is the shortest path to a custom agent with the same tools, permissions and context handling. Useful for internal bots and CI agents.

10. 10Specialised subagents in Claude Code

    Use case · Effort: Low

    Verdict: Subagents keep the main session's context clean and give specialised tasks their own instructions and tools. A practical first step into multi-agent setups with almost no code.

11. 11Deterministic guardrails with Claude Code hooks

    Use case · Effort: Medium

    Verdict: Hooks turn 'please remember to run the formatter' into a guarantee. Use them for anything that must always happen, rather than hoping the model remembers.

12. 12Building effective agents: the patterns

    Use case · Effort: Low

    Verdict: Required reading before you build a multi-agent system. Its core advice: start with the simplest pattern that works and add complexity only when it clearly helps.

13. 1312-Factor Agents

    Use case · Effort: Low

    Verdict: A practical checklist for moving from demo to production: own your prompts, own your control flow, keep state explicit. Opinionated and useful.

14. 14E2B sandboxes for agent code execution

    Tool · Effort: Medium

    Verdict: If your agent writes and runs code, run it in a sandbox, not on your server. E2B is a common choice with SDKs for Python and JS.

15. 15Dify

    Tool · Effort: Medium

    Verdict: A strong option when you want a visual builder for agent workflows and RAG with team collaboration, without stitching frameworks together. Self-hostable for data control.