swytchcode-examples: a tour of Swytchcode's agent templates
Swytchcode demo projects with different agents
At a glance
- What is it?
- Swytchcode's examples repository collects thirteen agent workflows, six of them scaffoldable from a CLI, across LangGraph, OpenClaw, CrewAI and the OpenAI Agents SDK. The templates are useful as starting points, but the real work of connecting your own APIs and credentials stays with you.
- Who is it for?
- Use swytchcode-examples if you already run LangGraph, CrewAI or the OpenAI Agents SDK and want a working skeleton for onboarding, payments, triage or reporting rather than a blank file. Skip it if you need a runnable end-to-end demo without third-party accounts, or if you expect the CLI to wire up credentials for you.
- Can I use it commercially?
- Yes. MIT is a permissive licence: you can use, modify and sell software built on it, as long as you keep its copyright and licence notices.
- Is it still maintained?
- Yes. The repository last received commits 6 days ago.
- What is it written in?
- Mainly TypeScript, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 15, 2026, and from our analysis. They are not legal advice.
DEEP OPEN-SOURCE ANALYSIS
What swytchcode-examples is for
The repository is a collection of demo projects built on Swytchcode, which its README describes as a standard for connecting autonomous agents to APIs, databases and tooling. The README frames the goal narrowly: starter templates, reference architectures and multi-API orchestration demos, with idempotency, audit trails and policy enforcement presented as properties of the underlying platform rather than of the examples themselves.
The audience is developers who already work with an agent framework and want a concrete project structure instead of an empty directory. The example list spans customer onboarding with HubSpot and Stripe, payment link generation, GitHub and Jira and Slack triage, lead qualification, weekly reporting, a refund agent, and a multi-user compliance workflow. Each entry names its framework and the third-party services it touches, so you can tell before cloning whether the demo matches the stack you have accounts for.
That last point matters more than the framing suggests. Every template is a multi-service workflow. If you do not have the named SaaS accounts, the template is a reading exercise, not a running program.
How the templates are organized and scaffolded
The README divides the directory into two groups. The first six examples can be scaffolded through the interactive CLI; the rest are reference architectures meant to be cloned and explored directly. That split is visible in the repository layout, where the scaffoldable set is dominated by LangGraph directories (customer-onboarding-langgraph, create-and-send-payment-langgraph, bug-escalation-langgraph, lead-qualification-langgraph, weekly-reporting-langgraph) alongside openclaw-swytchcode.
The remaining directories are a mix of frameworks and languages: fintech-compliance-multiuser-langgraph, Stripe-Subscriptions, langswytch, swytchcode-refund-agent-openclaw, star-repo-openai-agents-python, github-agent-crewai-python, github-issue-integration, plus several directories present in the tree but absent from the README table, such as gmail-assistant-anthropic-typescript, gmail-google-calender-openaisdk-demo, langgraph-google-calendar and zoom-swytchcode-demo. Those four are not described in the README's project directory, so treat them as undocumented until their own files say otherwise.
The primary language of the repository is TypeScript, but the table makes clear that Python examples exist too, and openclaw-swytchcode is listed as Go. If you are looking for a single-language codebase to vendor into your own project, this is not it.
Installing the CLI and scaffolding a first demo
The README's quick start assumes Node.js is already present. It gives one global install command, then an interactive generator. The generator asks for a use case and a framework, and writes a project directory for you. Nothing about credentials or environment files is handled by the CLI step itself; the README pushes that to the generated project's own README.
Install the CLI globally:
npm install -g swytchcodeLaunch the interactive project generator:
swytchcode examplesAfter the generator finishes, the README instructs you to change into the scaffolded directory and follow that project's README for setup and run steps. The repository does not document what the generated directory contains, which dependencies it installs, or which environment variables it expects. You will find those answers only inside the scaffolded project.
cd <your-scaffolded-demo>For the examples that cannot be scaffolded, the path is a plain clone. The README does not give a clone command, but the directory names in the table map directly to top-level directories, so the repository layout is the authoritative index for those.
Where the examples stop and your work begins
The honest limitation is that these are templates, not turnkey agents. Every scaffoldable example depends on external services: HubSpot, Stripe, Resend, GitHub, Jira, Slack, Sheets, Notion. The README lists them as tags, which tells you what the demo touches but not what it requires you to configure. There is no section on obtaining API keys, no sample environment file shown in the README, and no statement about which services have free tiers.
A second limitation is version drift. The latest release is dated 2026-07-03 and the last push to the repository was 2026-09-10, so the code is recent, but the README's quick start describes only the CLI path. It does not state which version of the CLI the templates were tested against, nor which Node.js version is required beyond "ensure you have Node.js installed." If a scaffolded project fails on install, the README gives you nothing to compare against.
Third, the framework coverage is uneven. LangGraph dominates the scaffoldable set. If you work in a framework that is not LangGraph, OpenClaw, CrewAI or the OpenAI Agents SDK, none of these examples is a drop-in starting point; at best you are reading the orchestration logic and rewriting the integration layer.
A real alternative: plain framework examples
The obvious comparison is the official example repositories maintained by the frameworks themselves, such as LangGraph's own examples or the OpenAI Agents SDK samples. The difference is in what is abstracted. Framework-native examples show the framework's primitives directly: graph nodes, tool definitions, state objects. Swytchcode's examples put a platform layer between the agent and the external service, which is where the idempotency and audit-trail claims come from.
That trade is the whole decision. If your problem is that an agent retried a Stripe charge or fired a duplicate Slack message, a layer that handles exactly that is worth evaluating. If your problem is that you do not yet understand how to wire a tool into a graph, the platform layer adds a concept you have to learn before you can debug anything. The README does not include a side-by-side comparison with either approach, so the choice has to be made from the code in the example directories rather than from the documentation.
Licence, maintenance and upgrade cost
The repository is MIT licensed, which is permissive: you can copy, modify and redistribute the example code, including in commercial projects, provided the licence notice is preserved. That applies to the example code in this repository. It does not automatically extend to the Swytchcode CLI or any hosted platform component, whose terms are not described in this README. If you plan to ship something derived from a template, check the licence of the CLI package separately from the licence of this repository.
The maintenance picture: the last push was on 2026-09-10, five days before this writing, and the repository is not archived. There is a CONTRIBUTING.md at the top level, which suggests external contributions are at least nominally accepted, though the README does not describe a review process or a release cadence.
Upgrade cost is the part the README does not address. Because each example is a standalone directory with its own dependencies, there is no shared version to bump. Adopting three templates means tracking three sets of dependency versions and three sets of third-party API changes. The README does not document rollback, migration notes or a changelog for the examples themselves, so a template you scaffold today has no documented upgrade path.
Editorial conclusion
Use swytchcode-examples if you already run LangGraph, CrewAI or the OpenAI Agents SDK and want a working skeleton for onboarding, payments, triage or reporting rather than a blank file. Skip it if you need a runnable end-to-end demo without third-party accounts, or if you expect the CLI to wire up credentials for you. Before adopting anything, open the README of the specific example directory you plan to copy, confirm which environment variables it expects, and check whether the repository's own setup steps still match the dependencies the template pins.
Frequently asked questions
What is swytchcode-examples used for?
It is a collection of demo projects and reference architectures showing how to connect AI agents to services such as Stripe, HubSpot, GitHub, Jira and Slack. Six of the examples can be scaffolded with the Swytchcode CLI; the rest are meant to be cloned and explored directly.
How do I install the Swytchcode CLI?
The README states you need Node.js installed, then run npm install -g swytchcode. After that, the interactive generator is started with swytchcode examples.
Which agent frameworks does swytchcode-examples support?
The project directory lists LangGraph, OpenClaw, CrewAI and the OpenAI Agents SDK, with LangGraph appearing most often among the scaffoldable examples. The primary language of the repository is TypeScript, though Python and Go examples are also present.
Can I run the examples without third-party accounts?
The README does not describe any offline mode, and every listed example names external services in its tags. Without accounts for those services, the templates are useful as reading material rather than runnable programs.
Community notes