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osherai

Pipedrive MCP Server

by osherai

get_activities

Retrieve activities such as calls, meetings, tasks, and emails from Pipedrive. Filter by linked entities, type, completion status, and date range to find specific records.

Instructions

Get activities (calls, meetings, tasks, emails) from Pipedrive.

Retrieves activities with various filter options. Can filter by linked entities, type, completion status, and date range.

Args: deal_id: Filter by deal ID person_id: Filter by person ID org_id: Filter by organization ID user_id: Filter by assigned user ID activity_type: Filter by type (call, meeting, task, email, etc.) done: Filter by completion status (True=done, False=not done) start_date: Activities from this date (ISO format: YYYY-MM-DD) end_date: Activities until this date (ISO format: YYYY-MM-DD) limit: Maximum results (default: 100)

Returns: JSON array of activities with subject, type, due date, done status, notes, and linked entities

Examples: - get_activities() - Get recent activities - get_activities(deal_id=123) - Get activities for a specific deal - get_activities(done=False) - Get incomplete activities - get_activities(activity_type="call") - Get all calls - get_activities(start_date="2026-01-01", end_date="2026-01-31") - Get January activities

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deal_idNo
person_idNo
org_idNo
user_idNo
activity_typeNo
doneNo
start_dateNo
end_dateNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description must cover behavioral traits. It mentions return format but does not disclose read-only nature, destructive potential, rate limits, or authentication requirements. Adequate but not fully transparent.

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 structured with sections (Args, Returns, Examples) and concise bullets. It is front-loaded with purpose. Slightly lengthy but efficient; a small reduction might improve.

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 0% schema coverage and no annotations, the description covers all parameters, return format, and provides examples. Lacks non-obvious constraints (e.g., pagination) but is complete enough for most use cases.

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?

Schema coverage is 0%, and the description adds detailed explanations for all 9 parameters, including types, defaults, and format (ISO date). Examples demonstrate usage, adding significant value beyond the bare schema.

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 it gets activities (calls, meetings, tasks, emails) from Pipedrive, with specific verb and resource. It distinguishes from sibling tools like get_deal or get_person by focusing on activities.

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?

The description lists numerous filter options and examples, implying when to use (e.g., to get activities for a deal, person, or by type). However, it does not explicitly state when not to use or contrast with alternatives.

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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