local-genai-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LOCAL_GENAI_MCP_CONFIG | No | Path to the configuration file (config.toml). The server searches for the config file in this order: the environment variable LOCAL_GENAI_MCP_CONFIG, then config.toml in the project folder, then ~/.config/local-genai-mcp/config.toml. The config file holds the Ollama and Forge Neo connection settings (base_url, default_model, output_dir, etc.). See config.example.toml for all options. If omitted, the defaults above are used. |
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
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| check_connectionsB | ローカル生成AIの設定・接続状況を返す(現在は設定エラー)。 |
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 1 tool
With only a single tool there is no risk of misselection between tools, so ambiguity is effectively zero. However, the name 'check_connections' is somewhat generic, leaving mild uncertainty about what exactly it inspects (config, network, model endpoints).
The lone tool uses a clear snake_case verb_noun pattern (check_connections), which is a readable, conventional style. Consistency cannot really be demonstrated with one tool, so it cannot earn a full 5.
A single diagnostic tool is far too thin for a server purporting to manage 'local generative AI' configuration and connections. There is no companion tool for configuring, listing models, or testing generation, so the surface is severely under-scoped.
The only tool returns status and currently reports a configuration error, with no way for an agent to set configuration, inspect available models, or run any inference. This is a dead end that will cause agent failures rather than enabling a workflow.