list_feedsList the curated cybersecurity feeds (id, title, category, source). Optionally filter by category (security) or keyword. Pass an id to read_feed.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Keyword to match in feed title/source/description. | |
| category | No | Filter by category: security. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "category": "security"
+ },
+ {
+ "query": "vulnerability"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly, idempotent, and non-destructive hints. The description adds that it returns specific fields but doesn't disclose pagination, rate limits, or ordering. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundant information. The purpose is front-loaded, and every sentence adds value.
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 lists returned fields. It also provides usage context (filter options and reference to read_feed). For a simple list tool with full annotation coverage, this is sufficient.
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?
The input schema fully describes both parameters (query, category) with 100% coverage. The description merely restates them without adding new semantic value, so baseline score of 3 applies.
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 action (list), resource (curated cybersecurity feeds), and output fields (id, title, category, source). It also distinguishes from siblings by mentioning read_feed for specific feeds.
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 tells when to use read_feed instead, implying a use case for detailed view. It also mentions optional filters. However, it doesn't explicitly exclude other scenarios or compare to other sibling tools.
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 ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded trio creates real selection ambiguity — beta is currently identical to the stable router, and grounded shares the same routing with an added evidence step. Polymarket tools also overlap (polymarket_edges vs polymarket_arbitrage both surface structural arbitrage), and entity_profile/recent_changes both pull filings and news.
Most tools follow a snake_case verb_noun pattern (resolve_entity, list_feeds, validate_claim, compare_entities). Minor deviations exist — bare verbs (remember, recall, forget, subscribe, unsubscribe) and noun-first names (entity_profile, recent_changes, pipeworx_trending) — but the overall convention is consistent and readable.
34 tools is excessive for a server nominally named 'Security Feeds' — only three tools actually relate to security feeds. Even as a broad data-research platform, the surface feels bloated with five near-exclusive Polymarket tools, three memory tools, and four subscription-lifecycle tools that could be consolidated.
For the actual domain revealed by the tools (data research, entity intelligence, prediction markets, subscriptions, feeds), coverage is strong: resolution, profiles, changes, comparison, claim verification, memory CRUD, subscription lifecycle, and feed operations are all present. Minor gaps include no subscription-update tool and no direct feed-search tool, but the ask_pipeworx router compensates.