Holaspirit MCP Server Overview

The Holaspirit MCP Server bridges the gap between AI assistants and the Holaspirit organizational platform. By exposing a Model Context Protocol (MCP) interface, it allows Claude and other AI agents to query, retrieve, and manipulate Holaspirit data without writing custom API wrappers. This integration solves the common pain point of manually exporting or scripting against Holaspirit’s REST endpoints, enabling developers to embed real‑time organizational insights directly into conversational AI workflows.

At its core, the server translates MCP tool calls into Holaspirit API requests. Developers can invoke high‑level actions such as , , or through a simple JSON payload. The server handles authentication via an API token, maps MCP tool names to the corresponding Holaspirit endpoints, and returns structured JSON responses that Claude can interpret as part of its context. This abstraction removes the need to manage pagination, rate limits, or data normalization manually.

Key capabilities include comprehensive coverage of Holaspirit’s core entities: tasks, metrics, circles, roles, domains, policies, and meetings. Each tool provides either a list view or a detailed lookup, giving AI assistants granular access to organizational structure and activity. The server’s design follows MCP best practices—explicit tool definitions, clear parameter schemas, and consistent error handling—ensuring reliable interaction for developers familiar with the protocol.

Real‑world use cases abound. A product manager could ask an AI assistant to “list all pending tasks in the Engineering circle” and receive an up‑to‑date snapshot, or a HR lead might request “details of the new role ‘Data Scientist’” to populate onboarding documents. Meeting coordinators can pull upcoming sessions, while analysts might query metrics across multiple circles to generate dashboards. In each scenario, the AI acts as a conversational UI that transparently pulls data from Holaspirit, reducing context switching and speeding decision making.

Integration into existing AI pipelines is straightforward. Once the MCP server is running, any Claude‑compatible client can declare the Holaspirit tools in its prompt. The assistant then invokes these tools as needed, and the server returns the data for further processing or presentation. This pattern keeps conversational logic in the AI while delegating data retrieval to a dedicated, protocol‑compliant service.

What sets this server apart is its zero‑code approach to connectivity. Developers can expose their entire Holaspirit dataset to AI assistants with a single configuration file, eliminating the need for custom middleware. The server’s lightweight implementation and adherence to MCP standards make it a plug‑and‑play solution for teams that already use Holaspirit and wish to augment their workflows with AI-driven insights.