AI assistants
MCP
Connect Claude, Cursor, ChatGPT-style tools, and agent runtimes through a protocol built for tool use instead of copy-paste workflows.
Claude DesktopClaude CodeChatGPTCursorWindsurf
YOUR AGENTS.
EVERY PLATFORM.
ONE INSTRUCTION.
MCP, REST API, or custom runtimes — your agent publishes to 9 platforms without touching a dashboard. One integration, everywhere you post.
MCP ProtocolAgent SkillsOpenClaw6 Platforms
Integrations
PICK THE PATH YOUR AGENT NEEDS.
Some teams want native MCP tool use inside an assistant. Some need a programmable backend for custom workflows. Some want an autonomous OpenClaw operator later. This page sets up all three.
🦞
Autonomous agentsOpenClaw
OpenClaw lets autonomous agents draft, schedule, and publish without leaving their runtime — no dashboard, no manual steps.
TelegramDiscordCLIAutonomous
Open source
Agent Skills
Install the PostMoore skill package directly into your agent runtime and get social publishing capabilities in your workflow instantly.
Claude CodeCursorWindsurfCodex
Custom agents
REST API
Build your own posting workflows with endpoints for posts, scheduling, media uploads, connected accounts, and Clipper Studio projects.
Node.jsPythonAll languages
Conversation flow
TELL YOUR AGENT WHAT TO POST.
The goal is simple: stop turning social distribution into a separate manual workflow. Your assistant or runtime should be able to reason, choose accounts, upload media, create drafts, and publish from the same thread.
Capabilities
EVERYTHING YOUR AGENT NEEDS.
The current product already gives agents the practical building blocks: posts, drafts, media uploads, account resolution, scheduling, and project workflows. This page packages that system as an agent-ready surface.
Multi-platform posting
Send one instruction and create social-ready payloads for multiple connected accounts at once.
Schedule and queue
Let your agent handle content timing, hold drafts, and trigger scheduled publishing without manual dashboard work.
Media uploads
Upload images and videos programmatically, then attach them directly to the posts your agent creates.
Account management
Resolve connected account IDs, check status, and target the right destinations from the same workflow.
Conversation-first ops
Treat publishing like an instruction stream instead of a dashboard task list. The agent asks, decides, and executes.
Per-platform results
Return result objects and failure details so your agent can retry, branch logic, or notify humans when needed.
Use cases
HOW AGENTS ACTUALLY USE THIS.
This is for shipping content from the tools you already live in: terminals, assistant chats, internal apps, autonomous loops, and custom control planes.
Agent workflow
Ship announcements from your terminal
Push code, tell your agent what changed, and let it turn the release into platform-specific posts without context switching.
Agent workflow
Run an autonomous content operator
Combine planning, media selection, scheduling, and publishing so your agent can move a content calendar forward on its own.
Agent workflow
Manage multiple brands or clients
Point one agent system at multiple connected accounts and let it choose the right caption, timing, and targets per brand.
Agent workflow
Plug posting into your own stack
Use the API to wire publishing into internal tools, pipelines, CRM triggers, release automation, or any custom backend.
Access
START WITH THE SAME POSTMOORE CORE.
This page is about access patterns, not a separate product line. The same PostMoore backend powers assistant workflows, API integrations, and OpenClaw.
Agent-ready setup
ONE ENTRY POINT.
MULTIPLE WORKFLOWS.
Register first. Expand later.
MCP + assistant workflows
Best when you want agents operating directly from chat with tool access and low setup friction.
API + custom runtimes
Best when you need your own orchestration, backend logic, and custom automation around publishing.
Go deeper
EACH PATH HAS ITS OWN PAGE.
`/ai-agents` is the overview. These pages break the stack down by protocol, docs, and the OpenClaw integration.
Protocol path
MCP
How PostMoore plugs into assistant runtimes that support tool calling through MCP.
Open route →
Technical reference
MCP Docs
Implementation details, expected workflows, and setup notes for connecting your agent stack.
Open route →
Autonomous path
OpenClaw
The OpenClaw integration for autonomous workflows that need social publishing built directly into the agent loop.
Open route →
FAQ
COMMON QUESTIONS.
The integration story is straightforward once you separate the protocol path from the backend path. This page is the framing layer.
Do I need a separate dashboard for agents?
No. The point of this page is the opposite: your agent should be able to act through MCP or the API and use PostMoore as the publishing backend.
What is the difference between MCP, the API, and OpenClaw?
MCP is the protocol path for AI assistants that support native tools. The API is for custom integrations and your own runtimes. OpenClaw is the autonomous-agent path — built for agents that need to reason, plan, and publish without human prompting.
Can my agent upload media before posting?
Yes. The public API already supports media uploads, then your workflow can reference returned media objects when creating drafts, scheduled posts, or immediate publishes.
Can I create drafts instead of publishing immediately?
Yes. Draft creation is part of the current API flow, which makes it possible to keep a human review step in the loop when you need one.
Where do I find setup guides for each integration?
Each path has its own dedicated page. /mcp covers the MCP setup, /mcp/docs has the technical reference, and /openclaw walks through the autonomous agent integration.
Final CTA
GIVE YOUR AGENT
A DIRECT PATH TO SOCIAL.
Connect your assistant or runtime through MCP, the REST API, or OpenClaw — and start publishing to every platform from a single instruction.