estonian-mcp

named_entities

Read-onlyIdempotent

Detect people, places, and organizations in Estonian text and return their entity types and character offsets, including inflected surface forms, for NLP extraction workflows.

Instructions

People, places and organisations (type PER, LOC, ORG) with character offsets start and end. text is the span as written, often inflected (Tallinnas).

Input Schema

Name	Required	Description	Default
`text`	Yes	Estonian text.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedv0.9.0Oct 24, 2026
- changedInput schema / properties / text / description
```
Previous value: -"Estonian text to extract named entities (people, places, organisations) from."New value: +"Estonian text."
```
- removedInput schema / properties / text / title
```
Removed value: -"Text"
```
- removedInput schema / title
```
Removed value: -"named_entitiesArguments"
```
- removedOutput schema / properties / result / items / additionalProperties
```
Removed value: -true
```
- removedOutput schema / properties / result / title
```
Removed value: -"Result"
```
- removedOutput schema / title
```
Removed value: -"named_entitiesOutput"
```
First observedv0.2.4Jul 5, 2026

TDQS

A3.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false. The description adds useful behavioral detail beyond those annotations by clarifying the returned fields (type, start, end, text) and warning that text is the span as written and often inflected, which matters for interpreting results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two compact sentences, front-loaded with the entity categories and offsets. Every phrase contributes useful information without repetition or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, read-only named-entity extraction tool with complete annotations, a complete input schema, and an output schema, the description is largely sufficient. It provides the entity types, offsets, and an inflection caveat; only explicit usage guidance is notably absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is only one input parameter, and schema description coverage is 100%, so the schema already documents the input adequately. The description mentions `text`, `type`, `start`, and `end`, but these appear to describe output fields rather than adding input-parameter semantics beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource as named entities by naming the categories (people, places, organisations) and corresponding types (PER, LOC, ORG). It does not state an explicit action verb or explicitly differentiate from siblings, but the tool name and unique entity-recognition focus make its purpose clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance about when to use this tool versus alternatives such as tokenize or pos_tag. It implies usage through the entity categories but does not state conditions, exclusions, or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.