Postoria MCP server is now available for AI agents

Postoria now has an official MCP server, making it easier to connect AI agents and MCP-compatible tools to your social publishing workflow.

The Postoria MCP server gives supported AI clients a structured way to understand your workspaces, connected social accounts, queues, media, and posts. Instead of manually copying details between tools, you can let an AI agent prepare parts of the publishing workflow through Postoria while keeping the final action clear and traceable.

You can use the MCP server in two ways. Local desktop clients can run the npm package, and MCP clients that support hosted MCP connections can connect to the Postoria hosted MCP endpoint at https://mcp.postoria.io/mcp. The server is open source on GitHub, available as an npm package, and documented in the Postoria MCP server help article.

What is MCP?

MCP, or Model Context Protocol, is a standard way for AI tools to connect to external apps and services.

For Postoria users, this means an AI agent can use Postoria actions through a supported MCP client. For example, it can list your workspaces, find connected social accounts, import media, schedule a post, add a post to a queue, or check a post status.

The goal is not to replace your publishing workflow. The goal is to make Postoria easier to connect with AI-assisted planning, automation, and content operations.

Works with MCP-compatible AI tools

The Postoria MCP server is designed for MCP-compatible clients and agents, including tools such as Claude Desktop, Cursor, Claude Code, and ChatGPT custom apps where custom MCP connections are available.

Local desktop clients can run the server from npm. MCP clients that support hosted MCP connections can connect to the Postoria hosted MCP endpoint. Hosted authentication depends on what the MCP client supports, including OAuth sign-in or Public API key bearer token authentication.

What the Postoria MCP server can do

The Postoria MCP server focuses on practical publishing workflows.

It supports tools for:

• Listing workspaces
• Listing social accounts in a workspace
• Listing queues in a workspace
• Importing media from a public URL
• Creating a signed media upload URL
• Completing a media upload after file bytes are uploaded
• Uploading local media files from supported desktop MCP clients
• Checking media status
• Publishing posts now
• Scheduling posts
• Adding posts to queues
• Listing existing posts
• Checking post status
• Deleting posts

This gives AI tools a focused set of actions around the core publishing flow: choose a workspace, choose accounts or queues, prepare media, create a post, and check the result.

Built on Postoria publishing workflows

The MCP server is built on top of the same publishing workflows available through Postoria’s Public API.

That means it supports the same core actions developers and teams use through the API: workspaces, social accounts, queues, media, posts, publishing modes, and post status checks.

The Public API and MCP server are available on Pro and Agency plans.

You can learn more in the Postoria Public API help article.

Local and hosted options

The Postoria MCP server can be used locally or through the Postoria hosted MCP endpoint.

With local usage, an MCP client such as Claude Desktop, Cursor, or Claude Code runs the npm package on your machine and uses your Postoria Public API key from the local MCP configuration.

With hosted usage, an MCP-compatible client connects to https://mcp.postoria.io/mcp. Depending on the client, authentication can use OAuth sign-in or a Postoria Public API key as a bearer token.

Both options connect to the same Postoria publishing workflows. The connection method depends on the MCP client you use and how it supports custom servers, authentication, and tool execution.

For setup details, read the Postoria MCP server help article.

Media workflows

The Postoria MCP server supports several media workflows, depending on where your media file already exists.

If the media is available through a public URL, the agent can import it into Postoria. This is useful when images or videos already live in a CMS, asset library, website, or another public location.

For API-style upload workflows, the server can create a signed upload URL. A client uploads the raw file bytes to that URL, then completes the upload so Postoria can process the media.

For desktop MCP clients, the server also supports local file upload. The MCP server can read the local file, upload it to Postoria storage, complete the upload, and return the media status.

Why this matters

Social media work increasingly involves AI-assisted planning, rewriting, repurposing, and workflow automation.

But publishing still needs structure. Teams need to know which workspace is being used, which social accounts are selected, which media is attached, when the post is scheduled, and what happened after publishing.

The Postoria MCP server gives AI agents a structured way to work with Postoria without turning publishing into a black box.

It is especially useful for:

• Agencies preparing posts across multiple clients
• Developers connecting internal tools to social publishing
• Teams experimenting with AI-assisted content operations
• Businesses that want to reduce manual steps between content planning and scheduling
• Power users who already use MCP-compatible desktop tools

Get started

You can explore the source code on GitHub, install the package from npm, or use the Postoria hosted MCP endpoint at https://mcp.postoria.io/mcp.

For local usage, configure your MCP client to run the Postoria MCP server package and pass your Postoria Public API key through the environment.

For hosted usage, add the Postoria hosted MCP endpoint to an MCP-compatible client that supports custom hosted MCP connections. Depending on the client, you can authenticate through OAuth sign-in or with a Postoria Public API key bearer token.

For the full setup guide, read How to use the Postoria MCP server.

Final thoughts

The Postoria MCP server gives AI agents a more reliable way to work with Postoria’s publishing workflow.

It connects AI-assisted planning with real social media operations: workspaces, accounts, queues, media, posts, statuses, and scheduled publishing.

This is another step toward making Postoria easier to connect with the tools teams already use, while keeping the publishing workflow clear, controlled, and connected to Postoria’s publishing infrastructure.