Semantic vector search over 787daily's Puerto Rico news corpus. Returns the most relevant article matches (title, URL, topic, date, score) for a free-text query — without generating an answer. Use this when you want matching articles rather than a synthesized answer; use ask() when you want a grounded narrative answer.
| Name | Required | Description | Default |
|---|---|---|---|
| topK | No | Max results to return (default 6) | |
| query | Yes | Free-text question or topic to search for |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool is a search that returns matches without generating an answer, and explicitly lists return fields. However, it doesn't mention any side effects or explicitly state read-only behavior, though it's implied by 'search'. This is good but could go further.
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?
The description is two sentences with no redundancy. The first sentence states purpose and output, the second gives usage guidance. Every word earns its place, and it's front-loaded with the core functionality.
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?
Given the tool's simplicity (2 params, no output schema), the description is complete. It names the return fields, explains the tool's behavior (search vs. synthesis), and provides usage context. No critical information is missing for an agent to select and invoke it correctly.
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 baseline is 3. The description does not add additional meaning beyond the schema; it only mentions 'free-text query', which matches the schema description. The topK parameter is not elaborated in the description, but the schema already covers it.
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 clearly states the tool performs semantic vector search over a specific corpus (787daily's Puerto Rico news) and returns article matches with specified fields (title, URL, topic, date, score). It also differentiates from ask() by noting it doesn't generate an answer, making the purpose unambiguous.
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?
Explicit guidance is provided: use this tool for matching articles rather than synthesized answers, and use ask() when a grounded narrative answer is desired. This clearly states when to use and when not to use, with a named alternative.
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.
Most tools have clearly distinct purposes: ask synthesizes answers, search_news does semantic retrieval, keyword_search_news does keyword matching, and the get_/list_ tools target specific data types. However, search_pr_news is a redundant alias, and get_by_entity vs get_by_municipality overlap on place queries, creating minor ambiguity.
Tool names use a mix of prefixes (get_, list_, search_) and include a bare verb (ask), which is not fully consistent. The legacy alias search_pr_news further deviates from the pattern, though the rest are readable and predictable.
With 13 tools spanning news, Q&A, weather, cost-of-living, and safety, the count fits the server's broad purpose without being excessive. Each major domain has dedicated tools, and despite one redundant alias, the set remains well-scoped.
The tool set covers article discovery, synthesis, weather, demographics, and safety statistics, providing solid domain coverage. Minor gaps include no full-text article retrieval and no dedicated section browsing, but summaries and links make these workable.