Swytchcode is a CLI execution layer that sits between your AI agent and production APIs like LangBase—handling authentication, retries, idempotency, and policy control so your agent can call real APIs safely instead of failing silently.

How do I get started with Swytchcode?

Run "npx swytchcode" to install the CLI—no account required. Then run "swytchcode get langbase" to pull the LangBase manifest and you're ready to call it from your agent.

How does an AI agent actually call the LangBase API through Swytchcode?

Your agent runs "swytchcode exec langbase. " with arguments. Swytchcode validates the call against the LangBase manifest schema, attaches your stored credentials, executes the request, and returns structured JSON your agent can act on—no auth or HTTP handling lives in your agent's code.

What happens if a LangBase call fails, times out, or hits a rate limit?

Swytchcode assigns every LangBase call an idempotency key and retries it automatically on transient failures or rate limits. If your agent re-runs the same action, Swytchcode recognizes the retry and prevents duplicate writes—a raw HTTP call wouldn't give you that safety net.

Can I restrict which LangBase actions my agent is allowed to run?

Yes. Policy rules in "tooling.json" let you allowlist or blocklist specific LangBase actions—for example, allow read-only calls but block anything destructive, or require approval above a threshold. Swytchcode enforces this before the call reaches LangBase, not after.

Where does Swytchcode store my LangBase credentials?

You authenticate once, and Swytchcode stores and refreshes your LangBase credentials server-side. Your agent—and the LLM behind it—only ever sees action names and results, never raw API keys or tokens.

Do I need to write a custom LangBase SDK integration for my agent?

No. "swytchcode get langbase" pulls a pre-built, versioned manifest describing every available LangBase action and its parameters, so your agent calls actions by name instead of you writing and maintaining request/response glue code.

How is calling LangBase through Swytchcode different from calling its API directly?

A direct call means you handle token refresh, retries, error parsing, and schema drift yourself, with no guardrails on what the agent can execute. Swytchcode does all of that and checks each call against your policy rules first, so an agent can't do something with LangBase you didn't explicitly approve.

Do I need a specific framework to call LangBase?

No. Swytchcode runs as a CLI or MCP server, so any agent, IDE assistant, or script can call it. Use the LLM and framework your team prefers.

Does Swytchcode log what my agent does with LangBase?

Yes. Every LangBase call—action, arguments, result, and timestamp—is written to a full audit trail, so you can debug unexpected agent behavior or review exactly what ran in production.

Get started

AI & Machine Learning

API Integration

LangBase API for AI Agents

Connect the LangBase API to your AI agent through Swytchcode. Call the LangBase API from the agent stack you already run. Swytchcode supplies the manifest, then handles authentication, retries, idempotency, and validation on every call.

Copy paste to your AI agent

Provider: LangBase
Category: AI & Machine Learning
License: Proprietary
Manifest: langbase
Official site: Not published
API docs: Not published

Use cases

What can you build with the LangBase API?

Call LangBase directly from an AI agent without writing custom auth, retry, or error-handling code.

Get the right endpoints and call sequence for the workflow you need, instead of having the agent explore the LangBase API surface.

Chain LangBase with other approved integrations in one workflow, each step validated against your policy before it runs.

Give an agent safe read/write access to LangBase in production, with idempotent retries if a call fails.

Setup guide

How to connect the LangBase API to an AI agent

Four steps, no SDK, no boilerplate. Every LangBase call routed through Swytchcode is idempotency-keyed and safe to retry.

1
Install the CLI
Run "npx swytchcode" to install the Swytchcode CLI—no account required to start.
2
Pull the manifest
Run "swytchcode get langbase" to pull the LangBase API manifest, including its schema and available actions.
3
Authenticate once
Provide your LangBase API credentials a single time. Swytchcode stores and refreshes them so your agent never handles raw secrets.
4
Call it from your agent
Run "swytchcode exec langbase.<action> --key value" from any agent or script. No SDK, no framework lock-in.

swytchcode get langbase
swytchcode exec langbase.<action> --key value

FAQ

Frequently asked questions

Hugging Face

Hugging Face integration available through Swytchcode.

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Deepgram

Deepgram integration available through Swytchcode.

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DeepL

DeepL integration available through Swytchcode.

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AssemblyAI

AssemblyAI integration available through Swytchcode.

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Build me a LangBase AI assistant

Copy the prompt into your agent. It will load Swytchcode and wire up LangBase.

LangBase API for AI Agents

What can you build with the LangBase API?

How to connect the LangBase API to an AI agent

Frequently asked questions

What is Swytchcode?

How do I get started with Swytchcode?

How does an AI agent actually call the LangBase API through Swytchcode?

What happens if a LangBase call fails, times out, or hits a rate limit?

Can I restrict which LangBase actions my agent is allowed to run?

Where does Swytchcode store my LangBase credentials?

Do I need to write a custom LangBase SDK integration for my agent?

How is calling LangBase through Swytchcode different from calling its API directly?

Do I need a specific framework to call LangBase?

Does Swytchcode log what my agent does with LangBase?

Other AI & Machine Learning integrations

Build me a LangBase AI assistant