holaspirit-mcp-server
by MCP-Mirror
This server provides MCP-compatible access to Holaspirit's API, allowing AI assistants to interact with your Holaspirit data through a standardized interface. It acts as a Model Context Protocol (MCP) server for accessing Holaspirit data.
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What is holaspirit-mcp-server?
This is an MCP (Model Context Protocol) server that provides access to the Holaspirit API. It allows AI assistants to interact with Holaspirit data through a standardized MCP interface.
How to use holaspirit-mcp-server?
- Install the server using
npm install holaspirit-mcp-server. 2. Configure your Holaspirit API token in a.envfile. 3. Start the server usingnpx holaspirit-mcp-server. 4. Refer to theexamplesdirectory for example usage.
Key features of holaspirit-mcp-server
Provides MCP access to Holaspirit API
Supports listing and retrieving tasks, metrics, circles, roles, domains, policies, and meetings
Offers a standardized interface for AI assistants to interact with Holaspirit data
Includes example scripts for demonstration
Use cases of holaspirit-mcp-server
Integrating Holaspirit data into AI-powered workflows
Building AI assistants that can manage tasks and metrics in Holaspirit
Automating Holaspirit-related processes using AI
Creating custom reports and dashboards based on Holaspirit data
FAQ from holaspirit-mcp-server
What is Holaspirit?
What is Holaspirit?
Holaspirit is a platform for organizational management and governance.
What is MCP?
What is MCP?
MCP stands for Model Context Protocol, a standardized interface for AI models to access external data.
How do I get a Holaspirit API token?
How do I get a Holaspirit API token?
You can obtain an API token from your Holaspirit account settings.
What are the available tools?
What are the available tools?
The available tools include list_tasks, list_metrics, list_circles, get_circle, list_roles, get_role, list_domains, list_policies, list_meetings, and get_meeting.
How can I contribute to the project?
How can I contribute to the project?
Fork the repository, create a feature branch, run tests and linting, commit your changes, push to the branch, and create a pull request.