Full-text search over titles, summaries and tags. Use this first when you know a name.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Query | |
| kind | No | Item kind | |
| limit | No | Default 20, max 100 | |
| collection | No | Collection slug |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It does add value by specifying the searched fields (titles, summaries, tags), but it does not disclose ranking behavior, matching semantics, read-only status, or pagination details. Inferred as read-only from 'search', but not explicitly stated.
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 brief sentences with no wasted words. The core function is stated first, and the usage guidance is placed second. Highly scannable for an agent.
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?
Adequate for basic invocation: the required parameter and filter semantics are in the schema, and the description gives usage context. However, there is no output schema and the description does not mention what the response returns or how results are ordered, so some gaps remain.
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 100%, so the schema already documents all parameters. The description adds modest value by clarifying that the query applies to full-text over titles, summaries, and tags, but it does not explain `kind`, `limit`, or `collection` beyond the schema.
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: full-text search over titles, summaries, and tags. This clearly differentiates it from sibling tools like feed_items, recent_items, and get_item, which are not search operations.
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?
Provides explicit guidance: 'Use this first when you know a name.' This tells the agent when the tool is appropriate, though it does not explicitly name alternatives or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are mostly distinct: list_* tools cover different metadata resources, and item queries are separated into recent_items, search_items, upcoming, and feed_items. Some overlap exists among the item-retrieval tools, but descriptions clarify their different filters and use cases.
Most tools follow a verb_noun pattern such as add_source, create_feed, list_* and search_items. A few exceptions like feed_items, stats, and upcoming break the pattern, but the overall naming is still predictable and readable.
Fifteen tools is well within the expected range and each tool maps to a distinct part of the domain: adapters, sources, collections, enrichers, feeds, items, and stats. The count feels appropriate for the breadth of NicheDB without obvious bloat.
The read and query surface is strong, covering items, feeds, sources, collections, and enrichers. However, lifecycle management is incomplete: sources and feeds can be created but not updated or deleted, and feeds can be followed but not unfollowed, which leaves notable admin workflow gaps.