Islam West Africa Collection (IWAC)

Find similar items

get_similar_items

Read-onlyIdempotent

The items nearest to a given one in meaning, by cosine similarity over the stored embeddings. Answers 'what else is like this' without a keyword — it finds pieces on the same event or theme that share no vocabulary. A neighbour above ~0.85 is usually the same story reprinted or lightly rewritten, which is how to spot syndication in this corpus; 0.6-0.8 is 'same subject, different piece'. Needs no API key: the item's own vector is a column, so nothing has to be embedded at request time. This is per-item, NOT the corpus-wide near-duplicate sweep — that is an all-pairs job and belongs offline.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	Item id — either a bare o:id ('3064') or the namespaced form search returns ('articles:3064')
`limit`	No	Neighbours returned (default 12, max 50)
`subset`	No	articles (default) \| publications \| references
`min_score`	No	Drop neighbours below this cosine similarity (0-1)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`note`	Yes
`view`	Yes
`source`	Yes
`subset`	Yes
`neighbours`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedJul 29, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

changedOutput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

Changed1 schema field changedJul 28, 2026

changedInput schema / properties / id / description

Previous value: -"The o:id of the item to find neighbours for"New value: +"Item id — either a bare o:id ('3064') or the namespaced form search returns ('articles:3064')"

AddedJul 28, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds valuable behavioral context: no API key needed, it's per-item (not corpus-wide), and explains what similarity scores mean. No contradiction with annotations.

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

Conciseness4/5

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

The description is two paragraphs with front-loaded main action. It is informative but slightly verbose; however, every sentence adds value. Could be more concise, but still good.

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

Completeness5/5

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

Given the rich annotations, full schema coverage, and output schema, the description is complete. It covers usage context, parameter interpretation, and behavioral traits sufficiently for an agent to invoke correctly.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds meaning beyond schema: it interprets the min_score parameter with concrete ranges (0.85+ syndication, 0.6-0.8 same subject) and clarifies the subset parameter implicitly. This helps agents choose appropriate values.

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

Purpose5/5

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

The description clearly states the tool finds items nearest in meaning by cosine similarity over embeddings, answering 'what else is like this' without keywords. It distinguishes itself from sibling tools like search or get_article by specifying it uses embeddings for semantic similarity.

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

Usage Guidelines5/5

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

The description explains when to use the tool (find similar items without keywords, identify syndication or same subject) and explicitly contrasts with the corpus-wide near-duplicate sweep, which belongs offline. It also provides guidance on interpreting similarity thresholds (0.85+ for syndication, 0.6-0.8 for same subject).

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

All Islam West Africa Collection (IWAC) tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.