Model Hub MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GOOGLE_API_KEY | No | Your Google API key | |
| OPENAI_API_KEY | No | Your OpenAI API key | |
| ANTHROPIC_API_KEY | No | Your Anthropic 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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_modelsC | List all available models from a specific provider |
| get_modelC | Get details of a specific model from a provider |
| list_all_modelsB | List all available models from all configured providers |
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 3 tools
The tools 'list_all_models' and 'list_models' have overlapping purposes that could cause confusion, as both involve listing models with only a subtle distinction (all providers vs. specific provider). The 'get_model' tool is distinct, but the ambiguity between the two listing tools is significant enough to risk misselection by an agent.
All tool names follow a consistent verb_noun pattern (get_model, list_all_models, list_models), using snake_case throughout. The naming is predictable and readable, with no deviations in style or convention.
With only 3 tools, the server feels thin for a 'Model Hub' domain, which might involve more operations like uploading, updating, or deleting models. While the count is not extreme, it borders on being under-scoped for the apparent purpose.
The tool surface is significantly incomplete for a model hub domain. There are no tools for creating, updating, or deleting models, and no operations for managing providers or configurations. This leaves obvious gaps that could cause agent failures in common workflows.