Skip to main content
Glama

search_universal

Search across all Pipedrive entities with a single query. Filter by item types or fields for targeted results.

Instructions

Search across all Pipedrive entities (deals, persons, organizations, products, leads, files).

Performs a universal search that can search across multiple item types simultaneously.

Workflow tips:

  • Search term must be at least 2 characters (1 if exact_match is true)

  • Specify item_types to limit search to specific entities

  • Use exact_match=true for precise searches

  • search_for_related_items=true includes up to 100 related items

  • Results include result_score for relevance ranking

  • Can search specific fields using the fields parameter

Common use cases:

  • Search everything: { "term": "acme" }

  • Search deals only: { "term": "contract", "item_types": ["deal"] }

  • Search persons and orgs: { "term": "john", "item_types": ["person", "organization"] }

  • Exact match search: { "term": "John Smith", "exact_match": true }

  • Search specific fields: { "term": "email@example.com", "fields": "email,phone" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termYesSearch term (min 2 chars, 1 if exact_match)
item_typesNoArray of item types to search
fieldsNoComma-separated field names to search
exact_matchNoPerform exact match search
search_for_related_itemsNoInclude up to 100 related items in results
startNoPagination start
limitNoNumber of items to return
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses search behavior (term length rules, pagination via start/limit, result_score for relevance) but does not explicitly state it's read-only (reasonable assumption). Could be improved by confirming no side effects.

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?

Well-structured with bullet points and labeled sections, but slightly verbose with repeated 'Search' in examples. Could be trimmed without loss of clarity, but still effective.

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 7 parameters, no output schema, and 100% schema coverage, the description covers key usage scenarios and parameter behavior. Mentions result_score but could detail response structure more. Lacking output schema is acceptable as per rules.

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?

While schema covers 100% of parameters, the description adds significant value by elaborating on usage (e.g., 'Term must be at least 2 characters (1 if exact_match)'), providing contextual examples, and explaining implications like related items limit.

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 'Search across all Pipedrive entities' and lists specific entity types. It distinguishes from entity-specific sibling tools like search_deals by emphasizing cross-entity search.

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 workflow tips (minimum character length, item_types usage, exact_match, related items) and common use cases with JSON examples. Effectively guides when to use different parameter combinations.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/iamsamuelfraga/mcp-pipedrive'

If you have feedback or need assistance with the MCP directory API, please join our Discord server