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MCP Intranet OnBotGo

@reyer3

Repository

Basic information

Category

Other

Transports

stdio

Author

reyer3

About MCP Intranet OnBotGo

Model Context Protocol (MCP) Server para administración inteligente de tareas del equipo OnBotGo. Integra APIs existentes de Apiaim e Intranet con capacidades de IA para gestión optimizada de proyectos.

#mcp-intranet#task-management#ai-integration

MCP Intranet OnBotGo config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-intranet-onbotgo": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP Intranet OnBotGo tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP Intranet OnBotGo?

MCP Intranet OnBotGo is a Model Context Protocol server that integrates OnBotGo’s existing Apiaim and Intranet APIs with AI capabilities for intelligent task management. It is designed for teams using OnBotGo to automate task creation, assignment, and project tracking.

How to use MCP Intranet OnBotGo?

Clone the repository, set up a Python virtual environment, install dependencies from requirements.txt, copy .env.example to .env and fill in credentials, then run python -m mcp_onbotgo.server.

Key features of MCP Intranet OnBotGo

  • Automatic task creation from natural language descriptions
  • Intelligent assignment based on workload and expertise
  • Automatic client and project detection
  • Dependency management and complex workflow support
  • Google Identity Toolkit and OAuth 2.1 authentication
  • Granular role‑based permissions and persistent sessions

Use cases of MCP Intranet OnBotGo

  • Create and assign tasks in a team project board via natural language
  • Automatically associate tasks with the correct clients and projects
  • Prioritize tasks and detect scheduling conflicts
  • Add contextual comments and update task progress through AI suggestions

Frequently asked questions

1

What authentication does it use?

It uses Google Identity Toolkit with OAuth 2.1 and granular role‑based permissions.

2

What are the runtime requirements?

Python 3, a virtual environment, and dependencies listed in `requirements.txt`.

3

Which APIs does it integrate?

It integrates OnBotGo’s APIs: BuscarClientes, CrearTareaEnTablero, ActualizarTareaEnTablero, and AgregarComentarioATarea.

4

Does it support persistent sessions?

Yes, it provides persistent sessions through MCP.

5

What is the target response time?

The server aims for an average response time under 200ms.

Comments

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