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Emdb

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

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false. The description adds value by detailing the fetching behavior, extraction of specific fields, and the standardized markdown output format, which helps the agent understand the tool's operation.

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?

The description is a single compact paragraph that front-loads the primary function and immediately provides actionable context. Every sentence contributes meaning, with no redundancy or filler.

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?

Despite no output schema, the description fully explains the output format ('single text blob ready to drop at site-root/llms.txt') and what is extracted. For a tool with only two parameters, this provides complete guidance for an agent.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds context: 'e.g., https://example.com or a specific landing page' for url, and 'default 25, max 50' for max_links. This clarifies defaults and usage patterns beyond the schema descriptions.

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 specifies the verb 'Generate', the resource 'llms.txt file', and the exact process: fetches page, extracts title/description/key links, and emits standard llms.txt markdown. It distinguishes from siblings by focusing on a specific output format and use case.

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 explicitly lists three concrete use cases: getting a client's site indexed, drafting for own project, and auditing a competitor. It provides clear context for when to use, though it doesn't explicitly state when not to use or name alternative tools.

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

Multiple tool clusters have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (the beta is explicitly the same right now); five polymarket_* tools all surface opportunity/edge information; entity_profile, compare_entities, and recent_changes all cover company research. The descriptions are detailed, but an agent can easily misselect between similar tools.

Naming Consistency4/5

All tool names use consistent snake_case and are descriptive, with clear prefix patterns for prediction-market tools (polymarket_*) and the router variants (ask_pipeworx_*). Some names are verb-noun while others are noun-phrases, but the convention is uniformly underscore-separated, with no camelCase or other mixing.

Tool Count2/5

33 tools is excessive for a coherent server, and the scope is sprawled across EMDB access, Pipeworx data routing, prediction markets, memory, subscriptions, and miscellaneous utilities. Even though each tool has a defined role, the sheer breadth and number make it feel like several servers' worth of functionality crammed into one.

Completeness2/5

The server's name suggests it should be focused on EMDB, but only two tools (get_map, search_maps) cover that domain — no browsing, filtering, or extended metadata beyond basic fields. Meanwhile, the bulk of the surface is devoted to unrelated Pipeworx/platform features. For the stated purpose, the coverage is severely incomplete.

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