Glossary

Remote MCP

What is Remote MCP?

Remote MCP refers to an MCP server that does not run locally on your own computer but is reachable over the internet via HTTP. The Model Context Protocol is an open standard that lets AI applications use external tools and data; for remote servers the specification provides the “Streamable HTTP” transport and authentication, for example via OAuth or an API key. The advantage is that a centrally hosted service is available to many users and AI programs without local installation.

How KI.ordo helps

KI.ordo provides such a remote MCP server under /mcp, reachable over HTTP with an API key, offering agents, flows and knowledge search as tools.

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Topics

MCP
interface
integration

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Related terms

Model Context Protocol (MCP)

The Model Context Protocol (MCP) is an open standard that lets AI applications access external tools, data sources and services in a uniform way. An MCP server provides functions, and an MCP client, such as an AI assistant, can call them. Anthropic introduced MCP in November 2024; since December 2025 it has been developed under the Agentic AI Foundation of the Linux Foundation (as of October 2026). This avoids building every integration separately.

interface
standard
+1

Intelligent Agents

An intelligent agent is a system that perceives its environment, processes information and chooses actions on its own in order to reach a goal. Today the term usually refers to software built on large language models that follows instructions, draws on knowledge and calls tools such as a search function or an API. How much an agent may do independently should be decided deliberately. Example: an agent answers customer questions using the product documentation.

Agents
Autonomy
+1

Extensibility

Extensibility is the ability of software to take on new functions, data sources or connections without rebuilding its core. Typical means are application programming interfaces (APIs), webhooks, plug-ins and open standards such as the Model Context Protocol (MCP). For businesses, an extensible AI solution works alongside existing systems such as a CRM or online shop and can grow with changing requirements.

Architecture
Interfaces
+1

Agentic

“Agentic” describes AI systems that do more than answer a single question: they pursue a goal over several steps, plan, use tools such as web search or APIs, check intermediate results and decide what to do next. An example is an assistant that categorises a request, looks up information and prepares a draft reply. Clear boundaries, logging and human approval at critical points are essential.

AI agents
Automation
+1