This Vercel AI agents guide explains how to install and use prebuilt agents from the Vercel Marketplace. You will learn what each agent does, how unified billing and onboarding work, and how to connect GitHub in one flow. It also shows when to add Services to scale, observe, and automate multi-step agent workflows. Vercel now ships “Agents” and “Services” as native building blocks. Agents do focused tasks for you, like code review and security checks. Services give you the foundation to build, test, and scale your own agents. The big win is speed. You install once, connect GitHub, and let the agent handle a clear job without extra dashboards or billing systems.

Why Vercel’s Marketplace changes AI agent adoption

Vercel’s marketplace removes common friction points. Teams used to juggle separate sign-ins, billing, and logs for each AI tool. Now the install flow, observability hooks, and billing live in one platform. Developers can start fast with prebuilt agents and later add Services for custom logic, testing, and orchestration. Here is what is new and useful:

One onboarding flow across agents and services

Unified billing and permission management

Built-in observability and workflow integration

Direct GitHub connection so agents can act on pull requests

At launch, the agent lineup covers code review and security. CodeRabbit checks pull requests and gives feedback on quality and best practices. Corridor watches your app for threats and alerts you early. Sourcery reviews and generates code to reduce bugs and security risks. All three connect to GitHub and start monitoring changes after setup.

Vercel AI agents guide: Installing and integrating prebuilt agents

This section gives you a simple path to install and run CodeRabbit, Corridor, or Sourcery with GitHub. The steps are similar across agents, because Vercel standardizes the flow.

Step 1: Pick your agent and read its scope

Open the Vercel Marketplace and choose an agent. Check the description to confirm what it does:

CodeRabbit: automated code review on pull requests

Sourcery: instant reviews and code generation to reduce bugs

Corridor: security monitoring with real-time detection

Look at each “required permissions” note. Make sure the agent’s scopes match the job it will do. Use least privilege. If it reviews PRs, grant repo read and PR comment permissions, not full admin.

Step 2: Connect GitHub in one flow

Click Install. Vercel will guide you through connecting your GitHub account or organization. You will:

Select GitHub repos or all repos (choose only what you need)

Confirm requested scopes

Finish the install back on Vercel

The agent will now track the selected repositories. It can scan new pull requests and push updates as comments or status checks, depending on its design.

Step 3: Configure agent behavior

Most agents provide simple toggles or settings. Start with defaults, then refine:

Choose which branches or folders to monitor

Set rules for review depth or severity levels

Customize the format of feedback comments

Enable notifications (Vercel, GitHub checks, or chat alerts)

Use clear rules. For example, block merge on “High severity” findings only. Let “Low severity” be advisory.

Step 4: Test on a sample pull request

Create a test branch and open a pull request with a small change. Watch the agent:

Confirm it triggers on new PR

Inspect comments for clarity and false positives

Measure time-to-feedback

Check that status checks reflect the correct pass/fail logic

Tune thresholds and filters after the test. Ask one teammate to try the same flow and report if anything is noisy or slow.

Step 5: Wire observability and alerts

Use Vercel’s built-in monitoring hooks so you can see when agents act and why. Route alerts to your team channel. Be mindful with alert fatigue:

Send only actionable alerts

Batch notifications for low-severity items

Create a weekly summary report for trends

If you need deeper testing and evaluations, add the Braintrust Service for systematic agent evaluation. More on Services below.

Step 6: Roll out to more repos and teams

Once the agent proves value on a small set of repos:

Expand to more critical services

Document norms for responding to agent comments

Measure impact on bugs, incidents, and lead time

Keep the rollout gradual. Do not “turn it on everywhere” on day one. Let teams learn the feedback style and adapt their code reviews.

Which agent should you start with?

Use this quick guide to match the agent to the job:

Pick CodeRabbit if you want consistent code reviews on PRs. It focuses on quality, security, and best practices feedback.

Pick Sourcery if you need both review and code suggestions to reduce bugs and speed up refactors.

Pick Corridor if your priority is real-time security detection and early threat alerts across your apps.

You can run more than one agent. For example, use CodeRabbit for review quality and Corridor for security monitoring. Start small, then stack where it adds clear value.

When to add Services for custom agents and scale

Agents are great for quick wins. Services help when you need to customize, test, and scale more advanced workflows. Services plug into Vercel workflows and CI/CD, and they work across your automation stack. Here are the Services available at launch and what they add:

Braintrust: test and monitor your custom agents with evaluation frameworks. Use it to measure quality and reduce regressions.

Kubiks: orchestrate multi-step workflows and auto-remediate issues before production. Think of it as a guardrail for agent actions.

Autonoma: run regression tests with AI and catch bugs before production. Setup starts with zero code.

Chatbase: analyze and tune conversational agents. Improve answers, reduce fallback rates, and spot gaps.

Kernel: give agents a managed browser in the cloud. Useful for tasks that need web navigation at scale.

Browser Use: turn natural language into real browser actions. Automate web tasks with an agent-controlled browser.

Combine Services with agents to build reliable and trackable production workflows. For example, pair CodeRabbit with Braintrust to measure review accuracy over time. Or link Corridor with Kubiks to auto-open tickets and run remediation steps when a security pattern appears.

Practical workflows you can ship this week

Let’s map two simple but high-impact workflows using the marketplace blocks.

1) Safer code review with automated gates

Goal: Reduce risky merges and speed up feedback.

Install CodeRabbit and connect selected repos.

Enable PR status checks and set rules for “High severity blocks merge.”

Add Braintrust to evaluate the agent’s reviews weekly. Track false positives and adjust rules.

Pipe alerts to your team channel and create a weekly summary with top issues by category.

Result: Developers get fast, consistent review notes. Leads can watch trends and improve standards. Merges slow only for severe issues.

2) Security detection with early remediation

Goal: Catch suspicious patterns before they hit production.

Install Corridor and connect your app repos.

Define environments and severity thresholds for alerts.

Add Kubiks to kick off a multi-step remediation when Corridor flags a critical pattern. For example, roll back a canary, open an incident, and ping on-call.

Log all events in your main observability tool via Vercel integrations.

Result: Teams see threats early and run a clear playbook with less manual work.

Setup checklist and policies that keep you fast and safe

Use this quick Vercel AI agents guide checklist to keep your rollout clean and compliant:

Start with 1–2 agents on 1–3 repos. Prove value first.

Grant least-privilege permissions on GitHub. Review scopes quarterly.

Define a triage rule for agent feedback. Who acts on what and when?

Turn on observability and tag all agent actions for easy tracing.

Review weekly trends: false positive rate, mean time to feedback, blocked merges count.

Write a short playbook: install, configure, test, roll out, and support.

Cost, governance, and onboarding tips

Unified billing helps finance and ops. Keep costs predictable with a simple policy:

Cap agent usage per repo at first. Expand after review.

Assign one owner per agent and per Service. Owners audit permissions and spend monthly.

Track business value: bug reduction, MTTR, time saved per PR, fewer security incidents.

For governance, store agent configs in version control. Use code reviews for config changes. If an agent can take actions, put a human-in-the-loop step for high-risk operations. For onboarding, run a short live demo: open a PR, watch the agent comment, and show how to act on it. Pair one senior dev with one junior dev for the first week to set good habits.

Front-end teams: connect agents with your app workflow

If your team builds with React and Next.js, the agent output can improve your developer experience. For example:

Show agent status in your PR templates so reviewers see the checks in one place.

Use feature flags to gate high-risk changes until agents pass.

Stream agent summaries to a dashboard in your internal Next.js app so teams see trends by repo.

If you deploy on the edge, note the wider ecosystem also moved forward. RedwoodSDK 1.0 Beta made it easier to build full-stack React apps on Cloudflare Workers with more predictable dev loops and first-class access to Durable Objects, D1, and R2. That pairs well with agent-driven CI, because faster edge apps benefit from cleaner code and fewer regressions.

Signals from the ecosystem: maps, frameworks, and developer demand

Google added Grounding with Google Maps to the Gemini API. This lets you build apps that use reliable place data, with an optional interactive widget for results. If your agents need geospatial context—say, for logistics or retail—this can improve accuracy and user trust. On the front-end side, React continues as the top framework in The Pragmatic Engineer 2025 survey, and Next.js leads meta frameworks. Tailwind CSS also sees strong adoption. For teams on Vercel, this means the path from agent insights to UI changes stays smooth and familiar. You can surface agent feedback directly in your dev tools and dashboards without switching stacks.

Troubleshooting common hurdles

Even with a clean install flow, teams hit a few recurring snags. Here is how to handle them:

Agent comments feel noisy: lower severity for non-blocking issues and batch minor comments into one summary per PR.

Slow feedback on large repos: scope the agent to specific folders first, like /api or /src/components, and expand later.

Conflicts with human review norms: align agent rules with your coding standards. Update your contributing guide with clear expectations.

Hard to measure value: define 2–3 KPIs before rollout. For example, average PR review time, percent of PRs with agent-only changes, or security alert reduction.

Document fixes and share them across teams. A small tweak in thresholds or scope often solves most pain.

From prebuilt to custom: a simple path forward

You do not need to design a custom agent on day one. Start with prebuilt agents, show impact, and refine your rules. When you need more control, plug in Services:

Use Braintrust to evaluate and track agent performance.

Use Kubiks to build reliable multi-step actions and remediation.

Use Autonoma to keep regression tests fresh without heavy scripts.

Use Kernel and Browser Use when your agent must browse and act on the web.

Use Chatbase to tune customer-facing agents and spot gaps.

This gradual path keeps your team fast and reduces risk. You ship value early and expand when the need is clear. Vercel brought agents and services into one marketplace with one install and one bill. That is why teams can finally adopt agentic workflows without extra tooling drag. Your job is to start small, wire good observability, and keep humans in the loop for high-impact actions. In short, this Vercel AI agents guide shows you how to install prebuilt agents, connect GitHub in one simple flow, and expand with Services when your workload grows.

(Source: https://thenewstack.io/vercel-marketplace-offers-agentic-ai-building-blocks/)

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