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Firecrawl

by io.github.pipeworx-io

Search

search
Read-onlyIdempotent

Run a web search via Firecrawl and return ranked results with URL, title, and description snippet. Takes a query string and optional limit (default 5, max 20). Returns {query, results[{url, title, description}]}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return (default 5, max 20).
queryYesThe search query, e.g. "best open-source vector databases".
_apiKeyNoOptional — your own Firecrawl API key for higher limits; omit to use the shared Pipeworx key.

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: +[
+  {
+    "query": "best open-source vector databases"
+  },
+  {
+    "limit": 10,
+    "query": "machine learning frameworks"
+  }
+]
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds useful context: return shape, default limit and max, and the fact results are ranked. This exceeds what annotations provide, though it doesn't mention rate limits or external API quirks.

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?

Two sentences with no fluff. Purpose, input, and output are stated efficiently.

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 simple search tool, the description covers purpose, parameters, and return format. No output schema exists, but the description explicitly defines the response structure. Combined with strong annotations, it is sufficiently complete.

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 coverage is 100%, so baseline is 3. The description repeats query and limit details already in the schema, and the _apiKey parameter is not mentioned in the description. The schema already handles parameter documentation.

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 it runs a web search via Firecrawl and returns ranked results with URL, title, and description snippet. The verb 'run' plus 'web search' specifies the action and resource, distinguishing from sibling 'search_within' which implies a different search scope.

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?

No explicit guidance on when to use this tool vs alternatives like search_within or scrape. The description implies usage is for general web search, but there are no exclusions or references to sibling tools.

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

All Firecrawl toolsInspect
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TDQS

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but the Polymarket analytics tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) have overlapping focuses that could confuse an agent if descriptions are not read carefully. Overall, detailed descriptions help differentiate them.

Naming Consistency5/5

All tool names are lowercase with underscores and follow a consistent verb_noun pattern (e.g., ask_pipeworx, bet_research, compare_entities). Prefixes like polymarket_ and pipeworx_ group related tools. No mixing of conventions or vague names.

Tool Count4/5

With 33 tools, the count is on the higher side but appropriate given the broad scope covering Pipeworx data access, Polymarket analytics, web scraping, memory, and subscriptions. Each tool has a distinct role, and the set is not overly bloated.

Completeness4/5

The tool surface covers a wide range of tasks: data queries, prediction market analysis, web scraping, memory, and subscriptions. Minor gaps exist, such as no tool for user account management or writing data back, but the core domain is well-covered with multiple specialized tools.

Resources