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Rcsb Pdb

by io.github.pipeworx-io

Generate llms.txt

generate_llms_txt
Read-onlyIdempotent

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL of the site to summarize, e.g. "https://example.com" or a specific landing page.
max_linksNoMaximum number of link entries to include (default 25, max 50).

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds process details: fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format, as well as noting that the output is a single text blob. This is useful beyond the annotations.

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

Conciseness4/5

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

The description is concise and well-structured, with a clear opening sentence, a brief process explanation, and a useful 'Useful for' list. Every sentence serves a purpose, though it could be slightly tighter.

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

Completeness4/5

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

For a simple two-parameter read-only tool with full schema coverage and strong annotations, the description explains the purpose, process, output format, and use cases. It does not discuss error handling or edge cases, but these are not essential given the tool's simplicity.

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?

Schema description coverage is 100%, with both url and max_links clearly described. The description does not add any parameter-specific semantics beyond what the schema already provides, so the baseline of 3 is appropriate.

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?

The description states exactly what the tool does: generates a production-ready llms.txt file for any URL, with a clear verb+resource+output format. It also distinguishes itself from siblings like scan_competitor_ai_presence by focusing on file generation rather than visibility checking.

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

Usage Guidelines4/5

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

The description provides explicit use cases: getting a client's site indexed, drafting llms.txt for your own project, or auditing a competitor. It does not explicitly name alternative tools or say when not to use it, but the use cases make the intended context clear.

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

A3.7/5.0
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical in purpose, and structure/summary both fetch PDB entries. The server name 'Rcsb Pdb' doesn't match most tools, which are Pipeworx data tools, compounding ambiguity.

Naming Consistency3/5

Mostly snake_case verb_noun, but verbs are inconsistent (ask, discover, generate, list, recall) and some names are noun phrases (entity_profile, polymarket_edges). No clear pattern unifies the set.

Tool Count2/5

37 tools is excessive for a server ostensibly about RCSB PDB; only 6 tools relate to PDB while 31 serve unrelated Pipeworx functionality. The count feels like a bundled grab-bag rather than a focused toolset.

Completeness3/5

The PDB-specific tools cover the core operations (search, fetch, assembly, ligand, polymer entity), so the structural biology surface is mostly complete. However, the server's overall purpose is muddled, and the Pipeworx tools are a separate domain that happens to be bundled in, making it unclear what 'completeness' even means for this server.

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