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meetergo

meetergo MCP server

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by meetergo

Crawl a website into the knowledge base

crawl_company_website

Ingest your company's website content into Mira knowledge base by crawling sitemap and same-origin links, extracting, chunking, and embedding readable text. Monitor crawl progress via status reads.

Instructions

Start a background crawl of a website into the company's Mira knowledge base, covering its sitemap and same-origin links while extracting, chunking and embedding readable text. Crawl progress remains available through status reads. Re-crawling an unchanged site ingests 0 new pages and is still successful. Requires the file-uploads entitlement (Growth and up).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesStart URL, e.g. the site root. Same-origin pages only.
languageNoKeep only pages in this 2-letter language, e.g. "de"
maxPagesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdNo
statusNo
messageNo
Install Server

TDQS

A4/5.0
Behavior4/5

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

Annotations already set readOnlyHint=false and idempotentHint=false, and the description adds valuable context beyond them: background execution, same-origin restriction, extraction/chunking/embedding pipeline, progress accessibility via status reads, and the idempotent behavior on unchanged sites. No contradiction 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.

Conciseness5/5

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

Three tight sentences front-load the primary action, then efficiently add status and re-crawl/idempotency details. No filler words; every sentence contributes distinct, useful information.

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?

An output schema exists, so return-value details are not needed in the description. The description covers background behavior, scope, re-crawl semantics, and prerequisites, giving an agent enough to invoke the tool correctly. The only minor gap is the unexplicated maxPages parameter, but the schema's min/max constraints partially mitigate that.

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?

The schema documents url and language with descriptions, and the description reinforces the 'same-origin' constraint, but it adds little parameter-specific meaning beyond that. The maxPages parameter is undocumented in both the schema and the description, leaving a 33% coverage gap unaddressed.

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 a specific action ('Start a background crawl'), an explicit target (a website into the company's Mira knowledge base), and the scope (sitemap and same-origin links). It clearly differentiates this ingestion tool from status, list, search, and other sibling tools.

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?

The description provides practical context such as re-crawling unchanged sites ingesting 0 pages and the entitlement requirement, which helps decide when to call it. However, it does not explicitly contrast with alternative ingestion or search tools, leaving some selection logic to inference.

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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