Skip to main content
Glama

Server Details

Multisyllabic, vowel and classic rhymes plus rhyming lines in 56 languages for lyrics and poems.

If you are the author of this connector, you can claim ownership by verifying the domain or GitHub account it belongs to. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
Status
Healthy
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

A3.9/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct outputs: find_rhymes returns rhyming words/phrases by rhyme type, while find_rhyming_lines returns complete real lines that end with a rhyme. There is no meaningful overlap in what an agent would select for a given task.

Naming Consistency5/5

Both names use a consistent snake_case verb_noun pattern with the same 'find_' prefix. 'find_rhymes' and 'find_rhyming_lines' are predictable and readable, with only a trivial grammatical variation in the noun phrase.

Tool Count3/5

Two tools is borderline thin for a rhyme-focused server. While each tool has a distinct purpose, the surface feels minimal and could benefit from additional related operations (e.g., syllable lookup or language filtering).

Completeness4/5

The server covers the core rhyme workflow: finding rhyme words by type and finding real rhyming lines for inspiration. Minor gaps exist, such as no explicit way to control language or look up syllable counts, but these are workable around.

Available Tools

2 tools
find_rhymesFind rhymesA
Read-onlyIdempotent
Inspect

Find rhymes for a word or short phrase. type "double" = multisyllabic rhymes (best for rap and poetry), "classic" = perfect end rhymes grouped by matching syllables, "vowel" = assonance (same vowel sounds). 50+ languages; strongest results come first.

ParametersJSON Schema
NameRequiredDescriptionDefault
typeNoKind of rhyme.double
wordYesWord or short phrase to rhyme on, e.g. "verloren" or "heart".
limitNoMaximum results per group.
languageNoLanguage code. Supported: af, ar, az, bg, bs, ca, cs, cy, da, de, el, en-us, eo, es, es_lat, et, eu, fa, fi, fr, fr_be, fr_ch, hi, hr, hu, hy, hy_arevmda, id, it, ka, kn, ko, la, lt, lv, mk, ml, ms, nl, no, pl, pt, pt_br, ro, ru, sk, sl, sq, sr, sv, ta, te, tr, ur, vi, zh ("en" = "en-us").en
vocabularyNo"rap" draws from rap lyrics (de and en only), "general" from general language.general

Output Schema

ParametersJSON Schema
NameRequiredDescription
typeYes
wordYes
groupsYes
languageYes
vocabularyYes

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety is covered. The description adds genuine behavior beyond that: results are ranked ('strongest results come first'), language breadth ('50+ languages'), and that classic rhymes are grouped by matching syllables. Only return-shape and rate/limit behavior are unstated, and an output schema exists.

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?

Two sentences, front-loaded with the core action, then the discriminating detail for each mode. No filler, no repetition of annotations or schema boilerplate.

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?

With an output schema present, return values need not be described, and the description covers the tricky parameter semantics, ranking, and language scope. The one gap is sibling differentiation against find_rhyming_lines, which an agent would need to resolve elsewhere.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description meaningfully expands the enum values beyond the schema's bare 'Kind of rhyme' — explaining double as multisyllabic, classic as perfect end rhymes grouped by syllable, and vowel as assonance. That is the kind of semantic lift the schema does not provide.

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?

States a specific verb and resource ('Find rhymes for a word or short phrase') and even clarifies the semantic variants of 'type'. It does not, however, differentiate itself from the sibling find_rhyming_lines, which remains a plausible alternative for an agent choosing a tool.

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

Usage Guidelines3/5

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

Usage is implied by the tool's obvious scope, and 'best for rap and poetry' gives parameter-level guidance, but there is no statement of when to prefer this over find_rhyming_lines or any exclusion. An agent must infer routing from the name alone.

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

find_rhyming_linesFind rhyming linesA
Read-onlyIdempotent
Inspect

Find real lines (lyrics, proverbs, sayings) that end with a rhyme on the given word. Useful as inspiration for the next line of a verse.

ParametersJSON Schema
NameRequiredDescriptionDefault
wordYesWord the lines should rhyme with.
limitNoMaximum number of lines.
languageNoLanguage code. Supported: af, ar, az, bg, bs, ca, cs, cy, da, de, el, en-us, eo, es, es_lat, et, eu, fa, fi, fr, fr_be, fr_ch, hi, hr, hu, hy, hy_arevmda, id, it, ka, kn, ko, la, lt, lv, mk, ml, ms, nl, no, pl, pt, pt_br, ro, ru, sk, sl, sq, sr, sv, ta, te, tr, ur, vi, zh ("en" = "en-us").en
vocabularyNo"rap" uses rap lyrics (de and en only), "general" uses proverbs and general texts.general

Output Schema

ParametersJSON Schema
NameRequiredDescription
typeYes
wordYes
groupsYes
languageYes
vocabularyYes

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and closed-world scope, so the safety profile is covered. The description adds useful content context (results are real lyrics, proverbs and sayings rather than generated text), but says nothing about result size, ranking, or how few lines may be returned for uncommon words.

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?

Two tight sentences with the mechanism (what it returns) front-loaded before the motivational use case. No filler, nothing redundant with the schema.

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?

An output schema exists, so return structure need not be explained, and annotations cover the mutation profile. For a one-required-param lookup tool this is nearly sufficient; only the relationship to the find_rhymes sibling is left unstated.

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?

Schema description coverage is 100% — word, limit, language and vocabulary all carry their own descriptions, including the supported language list and the rap/general enum distinction. The description adds only the vague phrase "the given word", so the baseline of 3 is appropriate.

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?

States a specific verb (find) and resource (real lines ending in a rhyme) with illustrative examples of source material. An agent can infer it differs from find_rhymes (which likely returns words), but the sibling is never named, so the distinction rests on inference.

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

Usage Guidelines3/5

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

"Useful as inspiration for the next line of a verse" implies the use case but gives no explicit when-to-use/when-not and never mentions find_rhymes as the alternative for a different need. Guidance is implied rather than stated.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updates
    • First observedfind_rhymes
    • First observedfind_rhyming_lines

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    Phonetic analysis engine that gives LLMs accurate rhyme detection, stress scanning, meter identification, and syllable counting backed by the full CMU Pronouncing Dictionary.
    5
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables users to find synonyms, rhymes, related words, autocomplete suggestions, and perform advanced word searches via the Datamuse API.
    74 npm
    1
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to explore a public-domain poetry collection by searching poems by title, finding poems whose lines contain a given phrase, pulling one or more random poems, and listing available authors. It returns full poem text with author and line-count details, and works either through a hosted gateway or as a local stdio server without an account.
    65 npm
    MIT
Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources