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Glama
feiskyer

MCP AI Hub

by feiskyer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

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

NameDescription
chatB

Chat with specified AI model.

    Args:
        model: Model name from configuration (e.g., 'gpt-4', 'claude-sonnet-4')
        inputs: Chat input (string or OpenAI-format messages)

    Returns:
        AI model response as string
list_modelsB

List all available AI models.

    Returns:
        List of available model names
get_model_infoC

Get information about a specific model.

    Args:
        model: Model name to get info for

    Returns:
        Dictionary with model information

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.3/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: chat for interacting with models, get_model_info for retrieving metadata about a specific model, and list_models for enumerating available models. There is no overlap or ambiguity between these functions.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (chat, get_model_info, list_models) with clear, descriptive verbs that align with their actions. No deviations or mixed conventions are present.

Tool Count3/5

With only 3 tools, the set feels thin for an AI hub server, potentially lacking operations like model configuration, session management, or advanced interactions. However, it covers basic listing, info retrieval, and chat functionality.

Completeness3/5

The tools provide core chat and model listing capabilities but have notable gaps for a full AI hub domain, such as updating model settings, managing conversations, or handling multimodal inputs. Agents can work around this but may encounter limitations.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources