lookupmacvendors.com = MAC address → hardware manufacturer (OUI) lookup; pass a full MAC or just the first 6 hex digits. Keyless; free tier is rate-limited to ~1 request/second.
| Name | Required | Description | Default |
|---|---|---|---|
| mac | Yes | A MAC address or at least the first 6 hex digits (the OUI). Separators (colons, hyphens, dots, spaces) or none all accepted, e.g. "FC:FB:FB:01:02:03", "FC-FB-FB", or "fcfbfb". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "mac": "FC:FB:FB:01:02:03"
+ },
+ {
+ "mac": "fcfbfb"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as read-only, open-world, idempotent, and non-destructive. The description adds key behavioral details: keyless access and rate limit (~1 req/s). No contradictions 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, front-loaded with purpose, no extraneous words. Efficient and easy to parse.
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 one parameter and no output schema, the description covers purpose, input format, rate limit, and keyless access. It does not describe response format, but for a simple lookup this is likely 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?
Schema coverage is 100%, with a clear description of the 'mac' parameter accepting various formats. The description reinforces that full MAC or first 6 hex digits work, but adds no new meaning 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?
The description clearly states the tool's purpose: MAC address to hardware manufacturer lookup via macvendors.com. It specifies the input (full MAC or first 6 hex digits) and output (manufacturer/OUI). Among sibling tools, none overlap, so there is clear distinction.
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 explains when to use the tool (MAC address lookup) and mentions it's keyless and rate-limited. While it doesn't explicitly list alternatives or when not to use, the context is sufficient given no similar sibling tools exist.
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.
Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same router, with the beta variant currently identical to stable. The five polymarket_* tools plus bet_research also blur boundaries, and discover_tools/suggest_questions both serve discovery. Detailed descriptions help, but an agent could easily select the wrong tool.
All names use lower_snake_case and many follow a clear verb_noun pattern (resolve_entity, validate_claim, generate_llms_txt). However, there are notable deviations: entity_profile, pipeworx_feedback, polymarket_edges, recent_changes, and bet_research lead with nouns or adjectives. The style is readable and predictable in clusters, but not uniform.
32 tools is well above the 25+ threshold for 'too many', and the server name Macvendors suggests a narrow MAC-lookup service, yet most tools belong to a much broader Pipeworx data/prediction-market platform. Several tools are near-duplicates or micro-variants (three ask_pipeworx versions, six polymarket tools). The set would be more appropriately split or heavily consolidated.
Within the actual broad research platform domain, the surface is fairly complete: discovery, routing, grounded answers, entity profiles, comparisons, recent changes, claim validation, semantic search, prediction-market analysis, subscriptions, memory, and feedback are all covered. Minor gaps exist, such as no subscription update tool and no batch MAC lookup, but agents can generally complete workflows without dead ends.