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Htmltext

by io.github.pipeworx-io

Extract Links

extract_links
Read-onlyIdempotent

Extract all hyperlinks from HTML as {href, text} pairs (keyless, offline).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
htmlYesThe HTML.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "html": "<html><body><a href=\"https://example.com\">Example Site</a><a href=\"/about\">About Us</a></body></html>"
+  },
+  {
+    "html": "<p>Check out <a href=\"https://github.com\">GitHub</a> and <a href=\"https://docs.example.com\">our docs</a>.</p>"
+  }
+]
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description adds 'keyless, offline' beyond annotations, indicating no API keys needed and no network calls. Annotations already cover readOnly and idempotent, so description enriches behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, direct, and front-loaded with purpose. No redundant words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Simple tool with one parameter, full annotations, and output described in the description. No missing information for correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Single parameter 'html' with baseline coverage 100%. Description adds no extra meaning beyond 'the HTML' and the tool's purpose; schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'extract' and resource 'hyperlinks from HTML', with output format '{href, text} pairs'. Distinguishes from sibling tools like 'extract_metadata' and 'html_to_text'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage is clear (extract links from HTML), but no explicit guidance on when to use versus alternatives or when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.8/5.0
Disambiguation2/5

Several tools have overlapping or nested roles: ask_pipeworx_beta is explicitly identical to ask_pipeworx currently, ask_pipeworx_grounded uses the same router, and polymarket_arbitrage/polymarket_edges both surface mispricings. ai_visibility_check and scan_competitor_ai_presence are also tightly coupled, making tool selection error-prone.

Naming Consistency3/5

Names are uniformly snake_case and mostly readable, but the pattern is mixed: verb-first names like extract_links and discover_tools coexist with noun-first product names like polymarket_edges and entity_profile, plus bare verbs like remember and forget. This breaks the predictable verb_noun convention.

Tool Count2/5

34 tools is far too many for a server named Htmltext, and most tools are unrelated to HTML processing. Even as a broad data-research server, the count exceeds the usual 3-15 sweet spot and includes meta-tools, near-duplicate query modes, and niche utilities that bloat the surface.

Completeness3/5

The set is unusually broad—covering data research, prediction markets, memory, subscriptions, HTML extraction, AI visibility, and package scanning—but no single domain is fully fleshed out. HTML tools only do extraction, prediction-market tools lack a simple market browser, and there is no general web fetch tool. Most gaps can be worked around via ask_pipeworx, but the surface feels like a grab bag rather than a cohesive lifecycle.

Resources