Skip to main content
Glama
sesonet

freelo-mcp-server

Official
by sesonet

Freelo Finish Task

freelo_finish_task
Idempotent

Finish a task to move it to a completed state while preserving all data. Reactivate it anytime when needed.

Instructions

Marks a task as finished/completed. Task is moved to finished state, preserving all data. Can be reactivated with freelo_activate_task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskIdYesTask ID to mark as finished. Get from freelo_get_all_tasks.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesTask ID
nameYesTask name
labelsNo
workerNoUser object
date_addNoISO 8601 date-time format (e.g., "2021-10-04T09:32:00+02:00")
due_dateNoISO 8601 date-time format (e.g., "2021-10-04T09:32:00+02:00")
state_idNoState ID: 1=active, 2=finished
project_idNoProject ID
tasklist_idNoTasklist ID
due_date_endNoISO 8601 date-time format (e.g., "2021-10-04T09:32:00+02:00")
priority_enumNoPriority: h=high, m=medium, l=low
date_edited_atNoISO 8601 date-time format (e.g., "2021-10-04T09:32:00+02:00")
tracking_usersNo

Schema Changelog

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

  1. First observedv0.5.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds useful behavioral context beyond that by stating the task preserves all data and can be reactivated, which tells the agent the operation is reversible and non-destructive.

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?

Two compact sentences with no filler. The core action is front-loaded, and the reversibility note is a valuable addition that earns its place.

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 single-parameter tool with a rich schema, output schema, and relevant annotations, the description is complete. It states the action, outcome, data preservation, and reversal path; nothing essential is missing for correct invocation.

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?

Schema coverage is 100% and the schema already documents taskId with its source (freelo_get_all_tasks). The main description does not add parameter-level meaning beyond the schema, so the baseline score of 3 applies.

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 uses a specific verb and resource ('Marks a task as finished/completed') and clarifies the state transition ('moved to finished state, preserving all data'). It also distinguishes this from the inverse sibling freelo_activate_task, so an agent can correctly separate the two lifecycle operations.

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 clearly implies this is the operation to use when completing a task and explicitly names freelo_activate_task as the reactivation counterpart. It does not list exclusions or alternative completion-related tools, but the lifecycle context is strong enough for an agent to call it appropriately.

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

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/sesonet/freelo-mcp-server'

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