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Glama
emgeee

MCP Ollama Server

by emgeee

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
list_modelsA

List all downloaded Ollama models

show_modelA

Get detailed information about a specific model

Args:
    name: Name of the model to show information about
ask_modelA

Ask a question to a specific Ollama model

Args:
    model: Name of the model to use (e.g., 'llama2')
    question: The question to ask the model

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.4/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap. 'ask_model' queries a model, 'list_models' enumerates available models, and 'show_model' provides metadata about a specific model. An agent can easily distinguish between these three distinct operations.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case. 'ask_model', 'list_models', and 'show_model' maintain perfect naming consistency throughout the set, making them predictable and readable.

Tool Count3/5

With only 3 tools, the server feels somewhat thin for interacting with Ollama models. While the tools cover basic operations, additional functionality like model management (e.g., pull, delete) or conversation history would be expected for a more complete surface.

Completeness4/5

The tools provide good coverage for core Ollama interactions: querying models, listing them, and getting details. However, there are minor gaps in model management operations (e.g., pulling new models, deleting models) that agents might need to work around for full lifecycle coverage.

Maintenance

ActivityInactive
ResponsivenessNo issues