OpenAI MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_costsB | Fetches OpenAI costs for the specified period. |
| get_projectsB | Fetches OpenAI projects for the current organization. |
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 2 tools
The two tools have clearly distinct purposes: get_costs retrieves financial data for a specified period, while get_projects fetches organizational project information. There is no overlap in functionality, making it easy for an agent to select the correct tool based on the task.
Both tools follow a consistent verb_noun pattern (get_costs and get_projects), using the same verb 'get' and snake_case formatting. This uniformity makes the tool set predictable and easy to understand.
With only two tools, the server feels thin and under-scoped for an OpenAI MCP server, which might be expected to handle more operations like managing models, generating completions, or listing usage. The limited count suggests incomplete coverage of the domain.
The tool set is severely incomplete for an OpenAI server, lacking core operations such as creating or managing projects, generating text or images, or accessing model details. This will likely cause agent failures when attempting common OpenAI-related tasks.