MCP Server Asset

This documentation describes how to interact with the Celonis MCP Server Asset, which enables AI agents to securely access and interact with Celonis data and insights through the Model Context Protocol (MCP).

Goals

The Celonis MCP Server Asset provides a standardized way for AI agents to leverage Process Intelligence capabilities. It delivers a growing set of ready-to-use tools that AI agents can use to:

  • Search for relevant information from your Celonis data models and knowledge bases
  • Get real-time process context including KPIs, metrics, and process insights
  • Trigger actions in external systems based on process intelligence
  • Write back decisions to Celonis to create feedback loops and improve process execution

Delivered securely via the MCP, this toolkit makes it easy to build sophisticated agents that leverage Process Intelligence within any MCP-compatible client, such as Claude Desktop, Postman, or custom applications.

How it works

The MCP Server Asset is a Celonis asset type that encapsulates a collection of tools configured within the Celonis Platform. The asset follows the MCP specification, which is a standardized protocol for enabling AI agents to securely interact with external data sources and services.

Architecture

  1. Create and Configure : In Celonis Studio, you create an MCP Server Asset and configure it with the tools you want to expose to AI agents. These tools can include data retrieval functions, insight generators, knowledge model queries, and more.
  2. Publish : Once configured, the asset is published, generating a unique MCP Server URL that serves as the endpoint for MCP clients to connect.
  3. Authenticate : MCP clients authenticate using either OAuth 2.0 (recommended for production) or Application Keys (suitable for development and testing). The authenticated client receives a token that grants access to the MCP Server Asset.
  4. Discover Tools : The MCP client discovers all available tools in the MCP Server Asset, including their names, descriptions, and input/output schemas.
  5. Execute Tools : AI agents can then call specific tools, passing the required parameters and receiving structured responses.

Rate Limiting

The API implements rate limiting to ensure fair usage and system stability:

  • Default rate limit: 500 calls per minute per asset