Duplicate entry. The same server (https://mcp.remem.me/mcp) is listed as Remember Me – Bible Verse Collections, kept up to date from the Official MCP Registry. To add verses to your own Remember Me account and get quizzed on them, use Remember Me – Bible Memory.
Browse published Bible verse collections for memorization — multilingual, free, spaced repetition
Scored across 3 tools
The three tools form a clean browse -> detail -> metrics progression with no overlap: browse lists/filters collections, detail returns verse text, metrics returns engagement stats. Each targets a distinct data shape.
Consistent verb_noun snake_case throughout (browse_collections, get_collection_detail, get_collection_metrics), with the get_ prefix clearly marking single-collection lookups.
Three tools is on the thin side, but each is genuinely necessary for a read-only public discovery surface and none is redundant. It is well-scoped rather than padded.
Browse, detail, and metrics cover the core read lifecycle for published collections; write operations are deliberately out of scope (handled by the authenticated Remember Me server, as referenced in the descriptions). Minor gap: no way to enumerate topics/languages for discovery without a search term.
Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity.
Use this when the user looks for Bible verses to memorize on a theme (e.g. hope, anxiety, forgiveness) or for a ready-made memory list, such as one for a church group.
Collections their publisher keeps out of Discover (listed false) are not returned;
get_collection_detail still opens them by id.
Each result includes the collection's raw cover image — the URL the publisher
set, or null if they set none (the app may still show an auto-generated cover when
null). This is the stored value, not the computed display image.
Args: search: Search term to filter by name, description, or publisher name. language: Language code, optionally with a region or script (e.g. "en", "de", "pt-BR", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| offset | No | ||
| search | No | ||
| language | No | ||
| ordering | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description instead spends its budget on non-obvious behavior: the invisible `listed`-false exclusion and the caveat that the returned `image` is the raw publisher value, not the computed display cover. Both are facts an agent could not infer from schema or annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose, then usage condition, then exclusions — the right order. The image-cover caveat runs three lines and could be tightened, and a few Args entries restate names the schema already shows, but nothing is filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only, five-parameter, zero-required browse tool with an output schema already documenting return shape, this covers everything an agent needs: intent, filtering semantics, pagination, sort values, and the one misleading return field.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must carry all parameter meaning and it does: it names which fields `search` matches (name, description, publisher name), gives language format examples including region/script forms, enumerates the ordering values with `-downloads` as default, and states the 1–100 limit range with default 20.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Opens with a specific verb+resource ('Browse published Bible verse collections') and immediately names the three supported operations (keyword search, language filter, popularity sort). The 'published' qualifier scopes it against the sibling get_collection_detail, which it names explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives a concrete when-to-use with the user's likely phrasing ('verses to memorize on a theme (e.g. hope, anxiety, forgiveness) or a ready-made memory list'). It also states the exclusion condition — collections with `listed` false are not returned — and points to get_collection_detail as the alternative that still opens them by id.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get full details of a published collection including all verse text, references, and topics.
The collection and each verse include a raw image — the URL stored by the
publisher, or null if none was set (the app may still display an auto-generated
cover when null). These are the stored values, not the computed display image, and
round-trip with create_collection / add_verse on the authenticated Remember Me
server (auth.remem.me) if you copy this collection.
Args: collection_id: The collection ID (from browse_collections results).
| Name | Required | Description | Default |
|---|---|---|---|
| collection_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds real value beyond them: it explains that the raw `image` is the publisher-stored URL (null when unset, even though a generated cover may display) and that values round-trip with create_collection/add_verse on the authenticated server. It omits any note on item limits, pagination, or read-side auth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Purpose is front-loaded in the first sentence and the image caveat follows in a compact block. The image explanation is slightly repetitive (stored vs computed display image stated twice) but each sentence carries information an agent would otherwise guess wrong.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return shape need not be described, and the description focuses on the one genuinely non-obvious field (raw image semantics) plus the parameter source. Nothing critical to calling it is missing, though it stays silent on scale/pagination of returned verses.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must carry the parameter — and it does, defining collection_id as 'The collection ID (from browse_collections results)', which adds provenance the bare integer schema lacks. It does not specify ID format or validity behavior, so it is not fully compensating.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource with scope: 'Get full details of a published collection including all verse text, references, and topics.' This implicitly separates it from browse_collections (list-level) and get_collection_metrics (aggregates), though it never names those siblings explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied rather than stated — the note that collection_id comes 'from browse_collections results' sketches a browse-then-detail workflow, but there is no explicit when-to-use, when-not, or named alternative. Adequate but leaves the agent to infer the routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get community engagement metrics: memorization progress, verse mastery, difficult verses, and activity stats.
Args: collection_id: The collection ID (from browse_collections results).
| Name | Required | Description | Default |
|---|---|---|---|
| collection_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so safety and repeatability are covered by structured data. The description adds the metric content but says nothing about permissions, result size, or time-window of the stats, which is the remaining behavioral gap for a metrics endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two compact parts: a front-loaded purpose sentence listing the metrics, then a short Args block. No filler, though the Args line mostly restates a parameter already visible in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, read-only tool with an output schema present, the description covers purpose, return content families, and parameter provenance — enough to invoke correctly. The only omission is guidance against the sibling get_collection_detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must carry the single parameter, and it does add real value by stating where collection_id comes from (browse_collections results). It does not restate the integer type or validity constraints, so it is not fully compensating, but for one parameter this is close to adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Get') and resource ('community engagement metrics') and enumerates the metric families returned (memorization progress, verse mastery, difficult verses, activity stats), so the agent knows exactly what it retrieves. It does not explicitly contrast itself with get_collection_detail or browse_collections, so sibling differentiation is left implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: it is a read of metrics for one collection, and the arg note 'from browse_collections results' hints at the workflow that produces the ID. There is no statement of when to prefer this over get_collection_detail, which is the most likely confusion given the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
get_daily_readingget_daily_readingcreate_collectiondelete_collectionupdate_collectionupdate_versedelete_collectionupdate_collectionupdate_versecreate_collectionbrowse_collectionsget_collection_detailget_collection_metrics
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