mcp-ai-assistant-iris
Provides web search and code execution capabilities using OpenAI models (gpt-5/o3), with features like model selection, reasoning effort, search context, conversation continuity, and optional code interpreter for data analysis.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-ai-assistant-irissearch latest advancements in quantum computing"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-ai-assistant-iris
An MCP (Model Context Protocol) server that provides web search and code execution capabilities using OpenAI models. The iris tool supports model selection (gpt-5/o3) and optional code interpreter for data analysis.
Named after Iris, the Greek goddess of the rainbow and divine messenger, who swiftly carries information between gods and mortals.
Installation
Using npx (Recommended)
Simply install and use the package from the official npm registry:
claude mcp add iris -s user -e OPENAI_API_KEY=your-api-key -- npx @mokemokechicken/mcp-ai-assistant-irisOr configure manually in Claude:
{
"mcpServers": {
"iris": {
"command": "npx",
"args": ["@mokemokechicken/mcp-ai-assistant-iris"],
"env": {
"OPENAI_API_KEY": "your-api-key"
}
}
}
}Related MCP server: MCP OpenAI Tools
Features
Model Selection: Choose between gpt-5 (default) and o3.
Web Search: Advanced web search capabilities with configurable context size
Code Interpreter: Optional code execution for data analysis and visualization
Conversation Continuity: Continue previous conversations using response IDs
Flexible Configuration: Customizable reasoning effort and search context
Usage
The iris tool accepts the following parameters:
Parameters
input(required): Your question or search querysearchContextSize(optional): Search context size - "low", "medium", or "high" (default: "medium")reasoningEffort(optional): Reasoning effort level - "low", "medium", or "high" (default: "medium")model(optional): AI model to use - "gpt-5" or "o3" (default: "gpt-5")useCodeInterpreter(optional): Enable code interpreter for data analysis (default: false)previous_response_id(optional): Previous OpenAI response ID for conversation continuity
Conversation Continuity
The iris tool supports conversation continuity through the previous_response_id parameter. This allows you to maintain context across multiple tool calls by referencing a previous response.
How it works:
Each
iristool response includes a Response ID in the format:[Response ID: resp_abc123xyz]Use this Response ID as the
previous_response_idparameter in subsequent callsThe AI will automatically continue the conversation with full context
Response Format:
When you call the iris tool, the response will include:
The main response content
A Response ID at the end in the format:
[Response ID: {response_id}]
Usage Example:
First call:
- input: "Tell me about machine learning"
- Response: "Machine learning is... [Response ID: resp_abc123xyz]"
Second call (continuing the conversation):
- input: "Can you give me some practical examples?"
- previous_response_id: "resp_abc123xyz"
- Response: "Based on our previous discussion about machine learning... [Response ID: resp_def456uvw]"Important Notes:
Validity Period: Response IDs are valid for 30 days from creation
Context Inheritance: Previous conversation history, tool calls, and reasoning are preserved
Cost Impact: Previous conversation tokens are included in the input token count
Instructions: System instructions are not automatically inherited and must be specified each time
Environment Variables
OPENAI_API_KEY: Required OpenAI API key
License
This project is licensed under the MIT License - see the LICENSE file for details.
This server cannot be installed
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