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Zoho_crm

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

A5/5.0
Behavior5/5

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

Annotations only give low-level hints (readOnly=false, etc.), but the description discloses crucial behavior: filing without an account returns a claim_token, passing that token later reads the status, the team reads digests daily, and signal directly affects roadmap. This goes far beyond what annotations alone convey, with no contradictions.

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 long but every sentence serves a purpose: purpose, examples, exclusions, token workflow, roadmap impact, rate limits, and cost. It is front-loaded with the core action and immediately followed by usage categories, making it easy to scan.

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?

For a feedback tool with no output schema, the description fully explains the return behavior (claim_token, status reading), expected message format, rate limit, and cost. It also tells the agent exactly how to describe issues in terms of Pipeworx tools/packs, which is essential for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description adds meaningful cross-parameter semantics, especially the claim_token lifecycle (file first, later pass the token as the only argument to read the reply). It also frames the context object as 'which tool, pack, or vertical' in a way that clarifies how to fill it.

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 phrase ('Tell the Pipeworx team something is broken, missing, or needs to exist') that clearly defines the tool's purpose. It distinguishes this feedback tool from sibling research and data tools by focusing on reporting issues/requests back to the Pipeworx team.

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 guidance by enumerating categories (bug, feature/data_gap, praise) and a clear exclusion: if the tool came from a different MCP server, file it there instead. It also notes rate limits and the 'doesn't count against quota' policy, helping agents decide when this tool is appropriate.

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

B3.3/5.0
Disambiguation2/5

The five Zoho CRM tools are well-differentiated, but the 31 Pipeworx/Polymarket tools create heavy overlap (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research all serve similar lookup purposes). Mixing two unrelated domains makes it easy for an agent to select a tool from the wrong group.

Naming Consistency2/5

The Zoho tools share a consistent zoho_ prefix, but the remaining 31 tools follow no clear convention—ask_pipeworx, bet_research, deep_research, entity_profile, forget, scan_dependency, etc. mix noun-first, verb-first, and bare verb patterns without a unifying scheme.

Tool Count2/5

36 tools is well beyond what a Zoho CRM server needs, and only 5 actually relate to Zoho CRM. The bulk are for unrelated data sources, prediction markets, memory management, and web generation, making the set feel bloated and unfocused.

Completeness2/5

The Zoho CRM surface includes create, get, list, and search, but omits essential operations like update, delete, and upsert. The other 31 tools cover a completely different domain, so the server fails to provide complete lifecycle coverage for its stated purpose.

Resources