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Glama

Mailchimp

by io.github.pipeworx-io

Send Pipeworx Feedback

pipeworx_feedback

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNobug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
contextNoOptional structured context: which tool, pack, or vertical this relates to.
messageNoYour feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
claim_tokenNoRead the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / claim_token
      Added value: +{
+  "description": "Read the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.",
+  "type": "string"
+}
    • removedInput schema / required
      Removed value: -[
-  "type",
-  "message"
-]
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only mark readOnly=false etc., but the description adds significant behavioral context: anonymous filing returns a claim_token, later lookup behavior, rate limit of 5 per identifier per day, daily digest review, and that it is free and does not count against quota. No contradiction with annotations.

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?

Longer than the minimum, but every sentence contributes operational nuance (rate limits, token flow, MCP-server exclusion). The purpose is front-loaded and the prose is well-organized. Could be trimmed slightly but the length is justified by the tool's complexity.

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?

Despite no output schema, the description fully covers submission types, exclusions, anonymous token retrieval, rate limits, and team-read cadence. An agent has everything needed to select and correctly invoke this tool versus alternatives.

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 baseline is 3. The description adds value for the `message` parameter by instructing users to describe issues in Pipeworx tool terms and avoid pasting end-user prompts, and clarifies that claim_token is used alone. This goes beyond the schema, earning a 4.

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 opens with a specific verb and resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It enumerates feedback types (bug, feature/data_gap, praise) and explicitly scopes the tool to Pipeworx-served tools, distinguishing it from sibling research/agent tools.

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?

Provides explicit when-to-use triggers (wrong/stale data, missing tool, praise), a clear when-NOT-to-use exclusion (tools from other MCP servers should be filed there), and operational guidance for using claim_token later. This is textbook usage guidance.

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.

Resources