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Glama

Pipedrive

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

A4.7/5.0
Behavior5/5

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

Annotations are all false and thus provide little safety/behavioral information. The description compensates richly by disclosing key behaviors: filing without an account returns a claim_token, passing that token later reads resolution status, rate limit is 5 per identifier per day, and tool is free/doesn't count against quota. No contradictions 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?

The description is longer than average but every sentence earns its place: use cases, exclusions, formatting guidance, token flow, rate limits, and cost. It front-loads the core purpose and organizes supporting details coherently. It could be slightly tightened, but it is dense and useful.

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?

There is no output schema, so the description must explain return values; it partially does by stating that filing without an account returns a claim_token and that passing it later returns status/resolution. It also covers rate limiting and scope. It does not explicitly describe the response when an account is present, but the conditional disclosure is sufficient for most agents.

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 schema already documents all parameters. The description adds extra semantic value by explaining the claim_token round-trip flow ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})'), which clarifies how to use that parameter in a way the schema doesn't fully convey.

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+resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' This clearly differentiates pipeworx_feedback from sibling tools like ask_pipeworx or discover_tools, which are for retrieval rather than reporting issues.

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?

The description provides explicit when-to-use guidance: use for bugs, feature/data gaps, or praise. It also states a clear exclusion: do NOT use for tools from other MCP servers, naming the alternative (file with that server). It even advises how to phrase feedback ('describe in terms of Pipeworx tools/packs').

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

A3.6/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, e.g., ask_pipeworx and ask_pipeworx_grounded are nearly identical, and entity_profile, compare_entities, and deep_research all perform multi-source lookups. An agent would struggle to distinguish between them.

Naming Consistency2/5

Naming conventions are highly inconsistent, mixing snake_case (ask_pipeworx), lowercase (deep_research), and prefixed patterns (pipedrive_, polymarket_, pipeworx_). No unified verb_noun pattern exists across the set.

Tool Count2/5

With 35 tools, the count is too high for a server named Pipedrive, which suggests a CRM focus. Many tools are unrelated to CRM (e.g., prediction market, weather, economic data), making the surface feel bloated and unfocused.

Completeness3/5

The Pipedrive subset lacks create/update/delete operations, leaving basic CRUD incomplete. However, the broader data lookup tools cover a wide range of domains (financials, drugs, patents), so overall coverage is moderate but not fully coherent with the server name.

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