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CrawlForge MCP Server

by mysleekdesigns
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

agent

Read-only

Plan searches, fetch and filter relevant pages, then synthesize a structured answer for any open-ended research question. No URLs needed—just prompt the agent to investigate and return concise, sourced results.

Instructions

Use this when you need an autonomous agent to research, navigate, and synthesise an answer from the web - no URLs required. The agent plans search queries, fetches and filters relevant pages, and returns a prose or structured answer. model:"pro" uses deep multi-source research. Hard limits: maxSteps<=10, maxUrls<=20, 120s wall-clock. Confirms before pro runs. Degraded-but-useful output if no LLM keys/Ollama. Not for a URL you already have (scrape) or a question one search answers (search_web). Pages that block a plain fetch are retried in the stealth browser automatically (at most 2 a run, URLs you name first; evidence marked via:"stealth"). Cost: 18 credits at most - 8, plus 5 per stealth retry that gets the page; a retry that is blocked again is free. Example: agent({prompt:"What are the top 5 MCP servers in 2025?", maxUrls:10})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsNoOptional seed URLs to include (max 20)
modelNo"default" = SamplingClient loop (no keys needed); "pro" = full ResearchOrchestratordefault
promptYesNatural-language task or question
schemaNoOptional JSON schema for structured output
maxUrlsNoMax URLs to fetch (hard cap: 20)
maxStepsNoMax fetch iterations (hard cap: 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv6.0.0
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / schema / propertyNames
      Added value: +{
+  "type": "string"
+}
  2. Changed1 schema field changedv5.0.4
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. First observedv4.10.0

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses hard limits (maxSteps<=10, maxUrls<=20, 120s wall-clock), confirmation before pro runs, degraded-but-useful output without LLM keys, automatic stealth retry behavior, and the full cost model. This is rich, non-obvious 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?

The description is dense but every sentence carries useful information: purpose, constraints, alternatives, fallback behavior, retry mechanics, cost, and an example. It is front-loaded with the core usage and flows logically from selection to behavior to limits.

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?

For a complex autonomous agent tool with no output schema, this description is complete: it covers input semantics, hard limits, cost, failure mode without LLM keys, stealth retry behavior, alternatives, and the shape of the return value ('prose or structured answer').

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%, so the baseline is 3, but the description adds meaningful parameter context: the pro model uses 'deep multi-source research', hard caps are restated as constraints, and the example shows how prompt and maxUrls interact. It does not merely repeat 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 names a specific task: an autonomous agent to research, navigate, and synthesise an answer from the web, and immediately clarifies that no URLs are required. It clearly distinguishes this tool from scrape and search_web by stating what it is not for.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance and explicitly names the alternatives: 'Not for a URL you already have (scrape) or a question one search answers (search_web).' It also specifies when to choose the pro model and explains behavior when LLM keys are absent.

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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