@lewinnovation/clockify-mcp-server

list_time_entries

Retrieve time entries from a Clockify workspace, filtered by user, date range, project, task, or tags. Use it to review tracked hours and in-progress work.

Instructions

Lists time entries for a user in a workspace. If user_id is omitted, the current API user is used.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspace_id": "<workspace_id>"
    },
    "name": "list_time_entries"
  }
}

Input Schema

Name	Required	Description
`end`	No	Range end (yyyy-MM-ddThh:mm:ssZ).
`page`	No
`tags`	No
`task`	No	Filter by task id.
`start`	No	Range start (yyyy-MM-ddThh:mm:ssZ).
`project`	No	Filter by project id.
`user_id`	No
`hydrated`	No
`page_size`	No
`description`	No
`in_progress`	No	Maps to in-progress query flag.
`workspace_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.5Sep 13, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It notes the default user_id behavior but says nothing about pagination (page/page_size params exist), filtering behavior, permissions, or what fields are returned. For a read tool with 12 params and no annotations, this is thin.

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?

Two concise sentences, front-loaded with the core purpose and the user_id default. No wasted words, though it could be slightly more informative without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 12-param list tool with no annotations and no output schema, the description is incomplete. It doesn't cover pagination, filtering capabilities beyond what's in the schema, or return structure, leaving significant gaps for an agent.

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

Parameters2/5

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

Schema description coverage is only 42%, so the description should compensate but doesn't. It only addresses user_id's default, leaving undocumented params like tags, hydrated, description, page, and page_size without explanation in either the schema or the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb (Lists) and resource (time entries) with scope (for a user in a workspace). It's distinguishable from siblings like create_time_entry or stop_running_time_entry, but doesn't explicitly contrast with other list_* tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage (listing time entries for a user/workspace) but gives no explicit when-to-use guidance or alternatives. It does clarify a default behavior for user_id omission, which is useful context.

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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