Manage scheduled social publishing, content generation, analytics, listening, and comments through Kadenzo.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
This server is confirmed live β we successfully called its tools/list endpoint directly (see the verified badge above). We haven't yet sandbox-tested the stdio install command below specifically, which is a separate, ongoing check.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Kadenzo MCP.
list_accountsList the social accounts connected to this Kadenzo workspace β returns each account id, platform, and username. Use the ids as account_ids when scheduling.
schedule_postSchedule a social post to one or more connected accounts for a FUTURE time (it publishes automatically). Set validate_only=true to check accounts/limits/timing without scheduling.
list_postsList your posts, newest first. Optionally filter by status (comma-separated, e.g. "pending,posted") and paginate with limit (1-100) and offset.
get_postGet one post: roll-up status, per-channel outcome, and any options/thread that were set on it.
update_postEdit a post that has not published yet β change content, accounts, time, media, options, or thread.
cancel_postCancel a scheduled post before it publishes. Already-published posts cannot be cancelled.
Kadenzo/kadenzo-mcp MCP server exposes Kadenzo Studioβs public API as Model Context Protocol tools. It is designed for agents that need to inspect connected social accounts, prepare content, schedule future posts, and review publishing results. Supported networks include Instagram, TikTok, X, LinkedIn, YouTube, Facebook, Pinterest, Threads, Bluesky, Mastodon, and Telegram.
The server supports the full lifecycle of scheduled posts. An agent can list accounts, schedule content for one or more accounts, validate a proposed schedule without creating it, list or inspect posts, update unpublished posts, and cancel scheduled posts before publication. Posts require a future scheduled time and publish automatically through Kadenzo.
The agent communicates with the local MCP process, which wraps Kadenzo Studioβs API. Account IDs returned by list_accounts are used when scheduling or interacting with account-specific operations. Local image and video files can be sent through upload_media; the resulting hosted URL can then be supplied to a scheduled post.
Content workflows can combine generate_content with schedule_post. Content generation accepts a topic and one of the supported platforms: Instagram, TikTok, Snapchat, Facebook, or YouTube. Analytics tools provide recent account-level engagement data or best-effort per-channel metrics for a scheduled post. get_best_times uses an accountβs engagement history, returns UTC hours, and requires the Professional plan or higher.
Social listening tools cover tracked keywords, mentions, listening analytics, and share-of-voice reporting. The server also exposes tools for creating, editing, pausing, and deleting DM automation rules, including funnel and contact usage information where provided by Kadenzo.
Install and run the server with Node.js 18 or later:
Create an API key in Kadenzo under Settings β API keys, then provide it to the process as KADENZO_API_KEY. The API is available on paid Kadenzo plans. Claude Desktop and Cursor use an MCP configuration entry with the npx -y kadenzo-mcp command and the API key in the environment section.
KADENZO_API_BASE is optional and overrides the default API endpoint, https://studio.kadenzo.app/api/v1. Restart the MCP client after changing its configuration.
Publishing is schedule-only; the material does not describe an immediate-post operation. Kadenzo API access requires a paid plan, and some features have plan restrictions: best-times requires Professional or higher, per-plan caps apply to listening keywords, and share-of-voice reporting is marked Enterprise. Comment posting is limited to Instagram, Facebook, and LinkedIn as listed by the project. Post analytics are best-effort per channel, while account analytics are described as the more reliable analytics surface.
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