planvortex-mcp

MCP serverCommunication

Schedule posts, read comments and answer messages across thirteen social networks.

Unavailable. This server has no hosted endpoint yet, so ahel can't serve it.

Connect ahel once, and every AI you use reads what you have installed.

From the project's README

As published by taliasoftworks/planvortexmcp in README.md.

The official Model Context Protocol server for PlanVortex. It lets an AI assistant — Claude Desktop, Claude Code, Cursor, VS Code — schedule posts, read the comment inbox and answer private messages across twelve social networks: Facebook, Instagram, Threads, LinkedIn, TikTok, X, WhatsApp, YouTube, Google Business, Bluesky, Discord and Telegram.

You need a PlanVortex app, and every plan has them — the free one included. The server authenticates with a client_id and a client_secret that you create in the PlanVortex panel under Settings → Apps. How many apps you get is what changes with the plan: 1 on Free, 2 on Basic, 5 on Pro, 10 on Custom.

Install

Nothing to install: your MCP client starts it with npx.

Claude Desktop, Cursor, VS Code

{
    "mcpServers": {
        "planvortex": {
            "command": "npx",
            "args": ["-y", "planvortex-mcp"],
            "env": {
                "PLANVORTEX_CLIENT_ID": "...",
                "PLANVORTEX_CLIENT_SECRET": "...",
                "PLANVORTEX_ORGANIZATION_ID": "optional, but saves a call per conversation"
            }
        }
    }
}

Claude Code

claude mcp add planvortex \
  --env PLANVORTEX_CLIENT_ID=... \
  --env PLANVORTEX_CLIENT_SECRET=... \
  -- npx -y planvortex-mcp

Then ask for something: "what do I have scheduled this week, and which comments are still unread?"

What it can do

Twenty-eight tools, grouped by what they act on — and a twenty-ninth, create_ai_plan, that you switch on yourself (see Generating with AI).

GroupTools
Contextlist_organizations, list_accounts, get_plan_use, get_unread_counts
Publishinglist_publications, get_publication, create_publication, update_publication, retry_publication
AI plannerget_planner_templates, list_ai_plans, get_ai_plan, and create_ai_plan when enabled
Mediaupload_media
Commentslist_comments, get_comment_thread, reply_to_comment, hide_comment, mark_comment_read
Messageslist_conversations, list_messages, send_message
Numbersget_dashboard_summary, get_publication_stats, get_top_publications, get_account_metrics
Catalogget_social_limits, get_social_capabilities, create_connect_link

Plus three prompts — weekly_plan, inbox_triage, publish_from_brief — and four resources with the per-network limits, capabilities, comment matrix and your organizations.

Generating with AI

PlanVortex does not just schedule what you wrote: it can write the week for you. Its planner turns a theme, your own photos, an article or a connected shop's catalogue into a week of posts, and get_planner_templates publishes the five templates with what each one costs.

Reading is always available. Creating a plan is not, unless you switch it on:

"env": { "PLANVORTEX_MCP_ALLOW_AI": "1" }

That is deliberate, and it is about your money rather than your safety. Generating a plan spends AI credits from your account, and an agent that retries in a loop is the worst possible caller for an endpoint that bills. The protocol's own answer to this — asking you to confirm from inside the server — is implemented by almost no client yet, so the confirmation is this line instead: a person writes it once, before any agent starts. With it absent, create_ai_plan is not in the tool list at all, so nothing can call it.

Two more things worth knowing. create_ai_plan does not return posts: it queues the plan and returns the budget, and generation takes minutes — poll get_ai_plan. And what comes out are drafts; scheduling them is still a person's decision, one post at a time, through update_publication.

Two things it deliberately cannot do

It never deletes anything. No tool removes a post, an account, a contact or a comment. This is not a switch you can turn on; the code is not there. The reason is in the security section below.

It cannot connect a social account. Connecting Instagram is an OAuth flow with a person clicking "authorize" on Meta's own screen, and an app with client credentials cannot do that — nobody's app can. create_connect_link returns a single-use link that expires in fifteen minutes; hand it to the user and let them open it.

Security

This server runs on your machine with your app's client_secret inside the process, and it feeds a language model text that members of the public wrote — comments, reviews, DMs — while that same model holds tools that publish under your brand.

That is a prompt-injection surface by construction, and it is worth knowing how it is handled:

  • Every comment, review and incoming message arrives wrapped in an untrusted_content block with an explicit notice that it is data, not instructions. It is not a guarantee — no wrapper is — but it raises the bar.
  • No destructive tools. If an injection succeeds, the worst case is a post you can see and delete, not four thousand deleted contacts.
  • Third-party text never enters a tool description or a cached resource, where your client would not mark it as untrusted.
  • Whether a publish is confirmed by a human is decided by your MCP client, not by this server. The tools declare the annotations that make clients show the warning; keep them on.

Set PLANVORTEX_MCP_READ_ONLY=1 to remove the nine write tools from the listing entirely — useful if you want to give an unsupervised agent read access and nothing else.

The --http mode

planvortex-mcp --http serves MCP over HTTP for a self-hosted deployment. The process holds your client_secret, so anything that can reach the port can publish to your accounts with a plain curl. Therefore:

  • it binds to 127.0.0.1 by default;
  • binding anywhere else requires PLANVORTEX_MCP_AUTH_TOKEN and the server refuses to start without it;
  • the Origin header is validated on every request (DNS rebinding);
  • TLS is your reverse proxy's job — put one in front;
  • and a token from the request is never forwarded to PlanVortex. It authenticates against this process and stops here.
docker run --rm -p 127.0.0.1:3000:3000 \
  -e PLANVORTEX_CLIENT_ID=... -e PLANVORTEX_CLIENT_SECRET=... \
  -e PLANVORTEX_MCP_AUTH_TOKEN=$(openssl rand -hex 32) \
  planvortex-mcp --http --host 0.0.0.0

The flags are not optional there: the image speaks stdio by default, because that is what an MCP client starts (docker run -i planvortex-mcp) and what a server directory introspects. --http is the deployment mode, and you ask for it.

Environment variables

VariableRequiredWhat it does
PLANVORTEX_CLIENT_IDyesThe app from your account. Every plan has apps.
PLANVORTEX_CLIENT_SECRETyesIts secret. Never passed as a tool argument.
PLANVORTEX_ORGANIZATION_IDnoDefault organization. Saves a discovery call per conversation.
PLANVORTEX_BASE_URLnoPoint at another PlanVortex deployment.
PLANVORTEX_MCP_UPLOAD_DIRSnoDirectories upload_media may read from. Empty means none.
PLANVORTEX_MCP_AUTH_TOKENwith --http off-loopbackBearer token the HTTP endpoint requires.
PLANVORTEX_MCP_READ_ONLYno1 removes the nine write tools.
PLANVORTEX_MCP_ALLOW_AIno1 adds create_ai_plan, which spends AI credits.
PLANVORTEX_MCP_LOG_LEVELnodebug, info, warn, error, silent. Always to stderr.

Uploading media

With stdio the server runs on your machine, so upload_media accepts an absolute local path — but only inside PLANVORTEX_MCP_UPLOAD_DIRS, which is empty by default. Set it to the folders you actually want reachable:

PLANVORTEX_MCP_UPLOAD_DIRS=/Users/you/Pictures,/Users/you/Downloads

Reading an arbitrary path is exactly what an injected prompt would ask for, so there is no way to disable the allowlist. In --http mode a local path is refused outright: it would be a path on the server, not on your machine. Pass a public https URL there.

Which organization?

Almost everything in PlanVortex hangs off an organization. The server resolves it in three steps: the id_organization argument if the model passed one, then PLANVORTEX_ORGANIZATION_ID, and finally — only if your app reaches exactly one — that one. If it reaches several and nothing says which, the tool answers with the list of names and ids so the model can retry correctly, rather than failing with a bare error.

Development

npm install
npm test          # layers 1 and 2: no network, no credentials
npm run build
npm run inspector # MCP Inspector against the built server

Built on planvortex, the official Node client. This server speaks no HTTP of its own: every call goes through the library, which is where the error catalogue, the token cache, the multipart upload and the pagination already live.

Links

MIT © Talia Softworks

Signals

Last commit
Sep 2026
Weekly downloads
157
Advanced
Delivery
planvortex MCP server → your ahel gateway (mcp.ahel.ai) → every connected AI client.
Catalog kind
mcp-server
Gateway key
io-github-taliasoftworks-planvortex
Source
github.com/taliasoftworks/planvortexmcp