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WarmInboxes Free MCP: Fleet Planner

by com.warminboxes
OverviewDiscussionsAdmin

Guides, playbooks, studies and videos

find_resources
Read-onlyIdempotent

Search what WarmInboxes publishes: operator notes (WarmInboxes' rules from running fleets, with the research behind them), cold email guides, deliverability playbooks, original studies and their datasets, costed infrastructure recipes, tool demo videos, inbox guides per sequencer and AI agent, provider comparisons, Claude skills, the changelog, the product pages (the ChatGPT plugin, the Claude connector, the MCP servers, the platform features, each with its current status), and the offer and about pages. Searches titles and full text, and each match carries the passage that best answers the query. It holds WarmInboxes' own studies as well as guides: 5 published studies, each with a stable WI-RESEARCH ID; type "study" lists every one, and https://warminboxes.com/research.json is the index. read_resource returns a whole page.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "find_resources"
  }
}

Input Schema

NameRequiredDescriptionDefault
typeNoOptional: only this kind of resource.
limitNoHow many matches, 1 to 10. Defaults to 5.
queryNoA question or topic, e.g. "warming up Azure inboxes" or "Smartlead".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint=false), so the description's job is to add behavior beyond that, and it does: it discloses that matching runs over titles and full text and that each hit carries the best-answering passage. It also notes the stable WI-RESEARCH IDs and the external research.json index, which the agent could not infer from fields alone.

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

Conciseness3/5

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

The first sentence is a single very long enumeration of content categories with parenthetical asides that buries the core action. The valuable parts (full-text search, best-passage results, study IDs, read_resource contrast) are there but compete with a catalog-style list that could be trimmed substantially.

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?

With three optional parameters and no output schema, the description carries the burden of explaining what comes back, and it does by saying each match includes the passage that best answers the query. Combined with annotations covering read-only semantics, an agent has enough to call it correctly; only result ordering and pagination behavior remain unstated.

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 description coverage is 100%, so the baseline is 3, but the description adds real semantics on top: it explains that the type filter selects a kind of resource and that type "study" returns the complete set rather than a ranked subset, and it clarifies the expected query shape. The limit behavior (1 to 10, default 5) is left entirely to the schema.

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?

States a specific verb and resource ("Search what WarmInboxes publishes") and enumerates the content it covers, so an agent knows exactly what corpus is being searched. It also explicitly separates itself from the sibling read_resource ("read_resource returns a whole page"), which is the main disambiguation an agent needs here.

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?

Gives concrete routing context: use this to find content and read_resource to get a whole page, and type "study" to enumerate all five studies. It stops short of explicit when-not-to-use guidance (e.g., that this is not the tool for internal account data or tool lookups like find_tools), so it is clear but not complete.

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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