read_feedRead a curated climate & energy feed by its id (from list_feeds). Returns normalized items (title, link, published, summary). Optionally filter items by keyword.
| Name | Required | Description | Default |
|---|---|---|---|
| feed | Yes | Curated feed id (from list_feeds). | |
| limit | No | Max items (1-50, default 20). | |
| query | No | Keyword filter over item title/summary. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "feed": "carbon-brief"
+ },
+ {
+ "feed": "iea-news",
+ "limit": 10,
+ "query": "solar"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, and non-destructive. The description adds value by stating the return format (title, link, published, summary) and the optional keyword filtering, providing clear behavioral context beyond 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?
The description is extremely concise: two sentences that front-load the core action and quickly convey the return format and optional filtering. No extraneous words.
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 no output schema, the description fully explains return fields. It also notes the limit and query parameters, and references list_feeds for ID sourcing. For a simple read tool, this is complete and self-contained.
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 100%, so the baseline is 3. The description adds minor reinforcement (e.g., 'from list_feeds' for feed) but does not significantly expand on what the schema already describes.
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 it reads a curated climate & energy feed by ID and returns normalized items. It references list_feeds to obtain the ID, making the function clear. However, it does not explicitly differentiate from the sibling tool 'fetch_feed', which may cause confusion.
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?
The description implies you need to use list_feeds first to get the feed ID, but it does not provide explicit when-to-use vs alternatives, nor does it mention when not to use this tool.
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 with thorough descriptions, but ask_pipeworx_beta is currently identical to ask_pipeworx, and the five polymarket_* tools plus three ask_pipeworx variants form overlapping clusters that could cause misselection without careful reading.
Names fall into recognizable families (list_*, read_*, fetch_*, polymarket_*, ask_pipeworx_*), but conventions are mixed: bare verbs like remember/forget, noun phrases like entity_profile/recent_alerts, and product-prefixed names. Predictable within families but inconsistent across the full set.
34 tools far exceeds the 25+ threshold and the typical well-scoped server. The bulk of tools—Pipeworx data access, Polymarket analysis, memory, subscriptions—go far beyond what a 'Climate Feeds' server name implies, making the set feel bloated and unfocused.
For its actual (much broader-than-named) scope, the surface is remarkably complete: query, grounded verification, research, comparison, entity resolution, memory, subscriptions, feedback, and discovery all exist. Minor gaps remain—subscriptions cannot monitor arbitrary RSS feeds, and there is no update operation for subscriptions.