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Mailchimp

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed5 schema fields changed
    • addedInput schema / properties / description
      Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}
    • addedInput schema / properties / q
      Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}
    • changedInput schema / properties / query / description
      Previous value: -"Natural language description of what you want to do (e.g., \"analyze housing market trends\", \"look up FDA drug approvals\", \"find trade data between countries\")"New value: +"Natural 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."
    • addedInput schema / properties / search
      Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}
    • addedInput schema / properties / task
      Added value: +{
+  "description": "Alias for query.",
+  "type": "string"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "look up FDA drug approvals"
+  },
+  {
+    "query": "analyze housing market trends"
+  }
+]
  3. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is clear. The description adds behavioral transparency by stating that results are 'ready to call directly, no second schema lookup needed,' which is useful context beyond the 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?

The description is concise yet comprehensive, fitting all essential information in a single paragraph. It front-loads the purpose, then covers usage, return value, and a call-to-action. Every sentence adds value with no redundancy.

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?

Given that there is no output schema, the description adequately explains that the tool returns 'top-N most relevant tools with names, descriptions, and full input schemas.' This covers the key output. It could mention pagination or error handling, but for a discovery tool this is sufficient.

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% with all 6 parameters described. The description adds value by explaining the aliases (task, q, search, description) and providing concrete examples (e.g., 'analyze housing market trends'). This enhances understanding beyond the schema alone.

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 clearly states the tool's purpose: 'Find tools by describing the data or task.' It lists many domains (SEC filings, FDA drugs, etc.) and explicitly distinguishes it from siblings by advising 'Call this FIRST when you have many tools available.' This makes the purpose specific and differentiated.

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?

The description provides clear when-to-use guidance: 'Use when you need to browse, search, look up, or discover what tools exist for...' and 'Call this FIRST when you have many tools available.' It implicitly suggests using this tool before using other tools, but does not explicitly state when not to use it (e.g., if the agent already knows the exact tool).

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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TDQS

B3.4/5.0
Disambiguation2/5

Several tools are near-duplicates: ask_pipeworx and ask_pipeworx_beta are currently identical, and discover_tools overlaps heavily with suggest_questions. The six Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, etc.) have fuzzy boundaries that will mislead an agent choosing among them.

Naming Consistency3/5

Most names are snake_case, but patterns vary: verb_noun (list_subscriptions, validate_claim), adjective_noun (recent_alerts, recent_changes), bare verbs (remember, recall, forget), and domain-prefixed tools (ask_pipeworx, polymarket_*, mailchimp_*). No camelCase mixing, but the inconsistency across styles makes prediction of names harder.

Tool Count1/5

The server is named Mailchimp but only 5 of 36 tools are Mailchimp-related; the remaining 31 tools cover unrelated domains (Pipeworx data lookup, prediction markets, memory, subscriptions). This extreme mismatch means the count is wildly inappropriate for the apparent purpose.

Completeness1/5

For a Mailchimp server, the surface is severely incomplete: only read operations exist (list/get audiences, campaigns, members) with no create, update, delete, send, or automation tools. The Pipeworx tools are comparatively rich but their presence does not fix the fact that the Mailchimp domain itself is a dead end.

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