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Introduction

Integrating with language models (LLMs) allows your tools and services (MCPs) to be consumed directly by conversational models such as ChatGPT, Claude, Cursor, or even by Agents and Assistants defined within the Devic platform. This turns your MCPs into live conversational extensions, capable of executing real functions from your SaaS or infrastructure when a model invokes them through natural language.

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Example: integration with ChatGPT

When a custom MCP is published through its URL, it can be made available to any language model compatible with the MCP standard.
This includes ChatGPT, which allows you to configure custom connectors and invoke tools directly through conversation. Example of MCP integration with ChatGPT – connector configuration

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How to enable it

  1. Go to the Connectors section in ChatGPT.
  2. Enable Developer Mode.
  3. Create a new custom connector by entering the MCP URL (e.g., https://mcp.devic.ai/suntropy-solar-service).
  4. Select the actions (tools) you want to expose.
  5. Save the changes — ChatGPT will now be able to communicate with your MCP.
Example of ChatGPT Developer Mode with MCP connected
💡 Tip: From this point on, ChatGPT can invoke your tools directly within the conversational flow, allowing users to interact with your SaaS via natural language.

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Example of real execution

Once the MCP is connected, users can ask natural-language questions such as:
“How many solar inverters do I have available?”
“Show me the summary of solar studies for September.”
The model, through the MCP, executes the corresponding tools and renders the visual results defined with widgets. Example of widget rendered inside ChatGPT with real-time data This not only displays data but can do so with your SaaS branding, thanks to widgets defined in Devic.

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Integration from Agents and Assistants

Beyond integration with ChatGPT or Claude, MCPs can also be consumed directly from Agents and Assistants configured in Devic.
This allows your internal automations, workflows, or enterprise assistants to benefit from the same integration capabilities as an external language model.
  • Agents can invoke MCPs within their task flows or scheduled executions.
    See the specific documentation:
    👉 Agents → Tools
  • Assistants can use MCPs during conversations or project integrations, showing interactive results or embedding widgets.
    See the specific documentation:
    👉 Assistants → Tools
Tool selection view from an agent in Devic

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Assistant configuring MCP tools in Devic

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Next steps

Agents

Learn how Devic agents can execute autonomous processes, make data-driven decisions, and orchestrate intelligent tools within your workflows.

Assistants

Discover how assistants enable real-time conversational interactions, integrating data and tools from your SaaS environment.

Databases

Explore how to create, query, and connect internal or vector databases to enhance agents’ and assistants’ reasoning capabilities.

Built-in Tools

Browse the complete list of integrated tools available in Devic and learn how to use them within your MCPs or custom agents.