parse_urlParse a URL into its components (keyless, offline): protocol, host, hostname, port, path, query (as an object), fragment, origin, and any userinfo.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | A full URL, e.g. "https://user@example.com:8443/a/b?x=1&y=2#frag". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "url": "https://user@example.com:8443/a/b?x=1&y=2#frag"
+ },
+ {
+ "url": "https://api.example.com/search?q=test"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, open-world, idempotent, and non-destructive behavior. The description adds 'keyless, offline', which clarifies no API keys or network calls are needed. This extra context is valuable beyond annotations, though it could mention behavior on invalid input or edge cases.
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?
Single sentence that efficiently and clearly conveys the tool's purpose and output. No extraneous information, well-suited for quick comprehension.
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, rich annotations, and complete schema coverage, the description adequately covers purpose and behavior. However, it lacks guidance on handling invalid or relative URLs, which would complete the context for edge cases.
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?
Only one parameter ('url') with full schema description coverage (100%). The schema includes examples and a clear description. The tool description does not add further parameter details beyond what the schema already provides, so baseline score of 3 is appropriate.
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?
Description clearly states the tool's function: parsing a URL into its components. It lists specific output components (protocol, host, hostname, port, path, query as object, fragment, origin, userinfo), making the purpose unambiguous and distinct from siblings like 'build_url' or 'parse_query'.
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?
No explicit instructions on when or when not to use this tool. While the description implies usage for extracting URL components, it does not mention alternatives like 'parse_query' for query-only parsing, or 'build_url' for constructing URLs. The agent must infer context from sibling names.
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 distinct, well-scoped purposes, but several question-answering/research tools sit close together: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim can all be selected for factual questions. The descriptions are detailed enough to reduce ambiguity, but ask_pipeworx_beta is currently identical to ask_pipeworx, and discovery helpers like discover_tools, suggest_questions, and pipeworx_trending also overlap somewhat.
Names are uniformly snake_case and mostly follow a verb_noun pattern such as build_url, list_subscriptions, resolve_entity, and validate_claim. The polymarket_* and pipeworx_* prefixes form a readable convention, though a few names like pipeworx_feedback and polymarket_arbitrage are noun-phrases rather than verb-first actions.
34 tools is well past the 25+ threshold where even a broad platform starts to feel bloated. The set mixes data research, prediction-market tooling, URL utilities, memory, subscriptions, feedback, and npm scanning, which would be more coherently split across focused servers.
The core research workflows are thoroughly covered: routing, grounded answers, deep research, entity resolution, comparisons, claim validation, discovery, alerts, and memory all exist. However, the URL utility and dependency-scanning side domains feel tacked on and incomplete, and there is no dedicated tool to fetch an arbitrary pipeworx:// citation record even though such URIs are returned throughout.