AI & Integrations

Use Relaycast from AI agents, coding assistants and no-code automation tools.

Relaycast is a plain REST API with JSON in and JSON out, so anything that can make an HTTP request can publish: an LLM agent with tools, a coding assistant writing an integration, or a workflow in a no-code tool. This section shows the quickest route for each.

Choose an approach

You want to...	Use	Guide
Let an LLM publish posts as a tool call in your app	Function calling with JSON-schema tools	Function Calling
Teach a coding agent (Claude Code, Codex, Cursor and others) how to use the API	A skill or rules file	Agent Skill
Give an assistant the docs as context	`llms.txt` and Markdown versions of every page	llms.txt & Markdown Docs
Publish from a workflow without writing code	An HTTP request step in n8n, Make or Zapier	No-code

Relaycast doesn't have an MCP server or an official SDK yet. Everything in this section uses the REST API directly, which every agent framework and automation tool already supports.

The three calls an agent needs

Almost every AI workflow uses the same three endpoints:

Step	Endpoint	Why
1. Find accounts	`GET /v1/accounts`	Get the `id` of each account to post to. Only `active` accounts can be published to.
2. Publish	`POST /v1/posts`	Send content, `targets` and either `publishNow: true` or `scheduledFor`.
3. Check results	`GET /v1/posts/{id}`	Read each target's `status`, `externalUrl` or `errorMessage`.

All three authenticate with the x-access-key header. See Authentication.

Guardrails for agents

Publishing is public and hard to undo, so put a few safety rails around any agent that can post:

Confirm before posting. Have the agent show the final text, accounts and time, and wait for a human to approve, at least until you trust the workflow. Scheduling a post a few minutes out gives you a window to delete it from the dashboard.
Use idempotency keys. Agents retry. Send an Idempotency-Key header derived from the task (for example the conversation or job ID) so a repeated tool call doesn't post twice. See Idempotency & Retries.
Keep the key server-side. The access key belongs in your tool executor or workflow credentials, never in the prompt, the model's context or client code.
Use a dedicated key and project. Give the agent its own access key, so you can revoke it independently and see its traffic in Request Logs. A separate project limits which accounts it can reach.
Feed validation errors back. A 400 validation_error lists problems per account and field. Returning that to the model lets it shorten text or fix options and try again.
Mind credits. Every target costs a credit. An agent stuck in a loop can spend them, so cap retries. See Credits & Usage.

What agents can't do through the API

Some things are dashboard-only, so plan for a human to do them:

Connecting OAuth accounts (Bluesky is the exception, it can be connected with POST /v1/accounts/bluesky).
Uploading files to the media library. Agents should pass public media URLs, or media:// references a person has prepared.
Editing, cancelling or deleting posts, and managing drafts, notifications, groups and collaborators.

Next steps

Function Calling: ready-made tool definitions for OpenAI and Anthropic
Agent Skill: a drop-in SKILL.md
API Reference: every endpoint in detail

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