# Markup AI — MCP server on mcp.ai
> Connect your Markup AI account and use 10 tools for artificial intelligence straight from your AI agent. Connect with your own API key. Markup AI provides content agents, brand terminology, personas, brand voice profiles, and style configuration for evaluating and improving content.

By: mcp.ai · official
Page: https://mcp.ai/markup_ai

## Connect (MCP protocol)
Remote MCP endpoint (HTTP, streamable): https://api.mcp.ai/p_markup_ai?ms=1787291340000
Add it as a custom/remote MCP connector, then authenticate when prompted.

## REST API (no MCP client required)
Every tool is also a REST endpoint, authed with a workspace API key.
Discover: GET https://api.mcp.ai/api/markup_ai/_endpoints   # public; lists every endpoint
Call:     POST https://api.mcp.ai/api/markup_ai/<endpoint>
  Authorization: Bearer sk_live_…   # create one at https://mcp.ai/settings/api-keys
  Content-Type: application/json
  Body: { …args }   →   { "ok": true, "tool": "<id>", "result": { … } }

## Developer docs
How to use (MCP or REST), markdown: https://mcp.ai/markup_ai/skill.md
Postman collection (v2.1): https://mcp.ai/markup_ai/postman.json

## Tools
- markup_ai_get_agent(agent_id: string) — Get one agent's metadata and complete runtime input and output JSON Schemas before executing it.
- markup_ai_get_analysis_profile(profile_id: string, profile_type: string) — Get one persona, brand voice profile, style target, or style guide by ID, including detailed configuration needed to understand its effect on analysis. Style details can contain a large hierarchy of g
- markup_ai_get_workflow(workflow_id: string) — Get the current status and result of an asynchronous agent workflow by ID.
- markup_ai_list_agent_categories() — Return all agent categories available to the connected organization for discovery and agent-list filtering.
- markup_ai_list_agents(category?: string, page_size?: integer, next_cursor?: string) — Discover Markup AI agents available to the connected organization, optionally filtered by category. Returns compact summaries for choosing an agent; use GET_AGENT for its full runtime schemas.
- markup_ai_list_analysis_profiles(profile_type: string) — List selectable persona, brand voice, style guide, style target, or content profile resources used to configure agent runs.
- markup_ai_list_terminology_resources(search?: string, page_size?: integer, domain_ids?: string[], has_context?: boolean, next_cursor?: string, resource_type: string) — List terminology term sets or domains with filters and cursor-controlled pagination.
- markup_ai_list_workflows(limit?: integer, status?: string, agent_name?: string, next_cursor?: string, created_after?: string) — List one cursor-controlled page of agent execution workflows, optionally filtering that page by status, stable agent name, or creation time.
- markup_ai_run_agent(url?: string, goal?: string, text: string, wait?: boolean, agent_id: string, domain_ids?: string[], persona_id?: string, webhook_url?: string, document_ref?: string, document_name?: string, style_guide_id?: string, voice_profile_id?: string, content_profile_id?: string) — Run one selected Markup AI agent against document text, synchronously or asynchronously. Discover the agent and inspect its schema first; execution may consume organization quota. The persona agent re
- markup_ai_search_terminology(text: string, domain_ids?: string[]) — Find organization terminology rules relevant to supplied text, optionally limited to selected domains.

## Example prompts
- "What can I do in Markup AI?"
- "Show me a summary of my Markup AI account"

## Links
Docs: https://mcp.ai/docs/mcps/markup_ai
Website: https://mcp.ai/mcps/markup_ai