Icelandic Morphology MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
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
| 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 |
|---|---|
| lookup_wordA | |
| get_variantA | |
| get_lemmaA | |
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
Each tool has a clearly distinct purpose with no overlap. get_lemma finds base forms from inflections, get_variant generates specific grammatical variants, and lookup_word provides comprehensive dictionary-style lookups. An agent can easily distinguish between analyzing forms, generating variants, and looking up entries.
All three tools follow a consistent verb_noun pattern (get_lemma, get_variant, lookup_word) with clear, descriptive names. The naming convention is uniform throughout the set, making the tools predictable and easy to understand.
Three tools is reasonable for a morphology server, covering analysis, generation, and lookup operations. While slightly minimal, each tool serves a distinct and essential function. A few additional tools (like batch processing or error handling) could enhance completeness, but the current count is appropriate for the core functionality.
The tool set covers the essential workflows for Icelandic morphology: analyzing inflected forms, generating grammatical variants, and looking up word entries. Minor gaps exist, such as batch processing or handling edge cases like compound words, but agents can work effectively with the provided tools for most tasks.