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Glama
cvanes

moa-mcp

by cvanes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

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

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_modelsA

List supported model providers and the models available under each.

Returns a mapping of provider name to a list of models, each with a
human-friendly name, the provider-specific model id to pass to
execute_prompt, and the input modalities the model accepts (text-only
models reject image attachments).
execute_promptA

Execute a single-turn prompt against a model and return its response.

provider and model_id must match an entry from list_models. attachments
is an optional list of local file paths (text or images) included as
context with the prompt.

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

A4.4/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have completely distinct purposes: one lists available models, the other executes prompts. There is no overlap or ambiguity in their functionality.

Naming Consistency5/5

Both tool names follow a consistent verb_noun pattern: 'list_models' and 'execute_prompt'. The naming style is uniform and predictable.

Tool Count3/5

With only 2 tools, the server feels thin for a typical MCP server, but the two tools cover a minimal end-to-end workflow (discover models, execute prompts). This is borderline acceptable but not a rich toolkit.

Completeness5/5

For the stated purpose of executing single-turn prompts against models, the surface is complete: list_models provides the necessary metadata to call execute_prompt, and execute_prompt handles the execution. No obvious gaps exist within this narrow scope.

Maintenance

ActivitySlowing
ResponsivenessNo issues

Resources