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Glama

Pipedrive

by io.github.pipeworx-io

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "key": "user_research_topic"
+  },
+  {}
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

The description adds meaningful context beyond the readOnlyHint and idempotentHint annotations by explaining that memory is scoped to an identifier (anonymous IP, BYO key hash, or account ID). This clarifies the memory model and isolation behavior. 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.

Conciseness5/5

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

The description is three sentences, front-loaded with the primary function, then usage context, then scoping. Every sentence adds value without redundancy, making it both concise and 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?

For a simple one-parameter memory retrieval tool with strong annotations and schema coverage, the description covers purpose, usage, scoping, and sibling relationship. No output schema is needed, and the description is complete for effective use.

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?

The schema already fully documents the optional 'key' parameter with the same omit-to-list behavior, and the description's mention of omitting the key is redundant. The description adds examples of typical key values but no new parameter semantics, so it stays at the baseline given 100% schema coverage.

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 function: retrieving a previously saved value via remember, or listing all keys when the key argument is omitted. It uses a specific verb ('Retrieve') and distinguishes itself from sibling tools like remember and forget by explicitly pairing with them.

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?

It explicitly says to use this tool for looking up previously stored agent context without re-deriving it, and mentions pairing with remember (save) and forget (delete). However, it does not list explicit exclusions or alternative tools for external lookups, so it is clear but not fully exhaustive.

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

All Pipedrive toolsInspect
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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.

Resources