MCP Agent Workflows
Postly MCP is for AI assistants that need to do real publishing work, not just suggest content.
What MCP gives an agent
With scoped Postly tools, an agent can:
- discover organizations and workspaces
- resolve connected publishing targets
- import media
- validate content against destination rules
- create or update posts
- schedule publishing
- inspect activity and analytics
Why MCP is different from direct API usage
MCP is useful when the actor is an assistant such as ChatGPT, Claude, Gemini, or another tool-using agent. Postly stays the secure execution layer while the agent gets a narrow set of governed actions.
Recommended agent workflow
- Resolve the right workspace first.
- Fetch the available channels or groups.
- Validate the content if the campaign is complex.
- Attach media during the same flow when possible.
- Create, update, schedule, or inspect the post.
- Report results back to the user clearly.
Where teams usually get value
- turning prompts into scheduled campaigns
- drafting then routing into approval
- handling generated media without manual re-hosting
- summarizing scheduled activity
- turning analytics into next-step suggestions
Guardrails that matter
Keep generation and execution close together
If the agent generates media or receives a temporary file reference, it should pass that media into Postly during the same turn or request flow where possible.
Keep workspace scope explicit
Agents should not guess the publishing destination. Resolve it.
Keep review in place where needed
MCP can speed up operations without removing approvals.