Skip to main content
Glama

Send That Email

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

TDQS

A4.4/5.0
Behavior5/5

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

While annotations already declare readOnlyHint=true, idempotentHint=true, etc., the description adds valuable behavioral context: it returns 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples)' and states results are 'ready to call directly, no second schema lookup needed.' This provides clear expectations of the output format and usability.

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

Conciseness4/5

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

Description is moderately long but front-loaded with the core purpose. Every sentence adds value: examples, return format, usage guidance. Minor redundancy in listing aliases could be trimmed, but overall well-structured.

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?

Given the tool's complexity (6 params, 1 required) and the absence of an output schema, the description fully covers what the tool does, when to use it, and what it returns. It explains that each result includes schemas and examples, making the tool self-contained. No gaps for the intended use case.

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 description coverage is 100%, so baseline is 3. The description does not add additional meaning beyond what the schema already provides (e.g., natural language description, aliases). The examples in the input schema help, but the description itself offers no extra parameter guidance.

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 verb+resource: 'Find tools by describing the data or task.' It lists numerous example domains and explicitly distinguishes from other tools by stating 'Call this FIRST when you have many tools available and want to see the option set.' This differentiates it from sibling tools like search_within or deep_research.

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?

Description explains when to use this tool (browse, search, look up) and contrasts with 'not just one answer,' implying it is for discovering options rather than getting a single answer. However, it does not explicitly name alternatives or state when not to use it.

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

All Send That Email toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer queries with subtly different guarantees. The Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_kalshi_spread, polymarket_edge_tracker) also has fuzzy boundaries. Despite detailed descriptions, an agent could easily pick the wrong tool.

Naming Consistency2/5

Naming conventions are inconsistent: there are verb_noun names (discover_tools, resolve_entity), noun-based names (polymarket_edges, pipeworx_trending), single verbs (remember, recall, forget), and odd constructions like send_that_email_analyze. No clear pattern dominates, making it hard to predict tool names.

Tool Count2/5

32 tools is heavy for a focused server, and most tools are unrelated to the server's apparent email-sending purpose. The count feels bloated and the scope mismatched, though it is not extreme enough for a 1.

Completeness1/5

Given the server name 'Send That Email', the tool surface is severely incomplete: there is only an email analysis tool and no actual sending, drafting, or mailbox management. The bulk of the tools address data lookup and research, leaving the core email workflow entirely unimplemented.

Resources