mcp-ai-assistant-iris
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPENAI_API_KEY | Yes | OpenAI API key |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| irisB | iris (v0.6.1): An AI agent with advanced web search and code execution capabilities. Supports model selection (gpt-5.1/gpt-5/o3) and optional code interpreter for data analysis. Useful for finding latest information, troubleshooting errors, and executing code. Supports natural language queries. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 1 tool
There is only one tool, so there is no possibility of selecting the wrong tool or confusing overlapping purposes. The single 'iris' entry point is unambiguous by construction, though it is broad by nature.
With a single tool named 'iris', there is no inconsistency to detect and the name is short and memorable. However, it follows no verb_noun or other recognizable convention, so a predictable pattern cannot be established.
A single tool for an entire server is very thin; all functionality (web search, code execution, model selection, data analysis) is collapsed into one monolithic call. This leaves no granular surface for an agent to compose or target specific capabilities.
As a general-purpose agent wrapper, the tool can cover a wide range of tasks via natural language, which partially compensates for its thinness. But there is no coverage of auxiliary lifecycle operations (sessions, memory, configuration) that an assistant server would typically expose.