Skip to main content
Glama
karbassi

slack-mcp

by karbassi

apps_activities_list

Retrieve activity logs for a Slack workflow app. Filter by severity, event type, or date range to troubleshoot issues.

Instructions

Get logs for a specified workflow app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of log entries to return.
app_idYesThe app whose activity logs to return.
cursorNoPagination cursor from a previous response's ``response_metadata.next_cursor``.
sourceNoOrigin of logs: ``slack`` or ``developer``.
team_idNoWorkspace to scope logs to (org-wide tokens).
min_log_levelNoMinimum severity: ``trace``, ``debug``, ``info``, ``warn``, ``error``, or ``fatal``.
component_typeNo``events_api``, ``workflows``, ``functions``, or ``tables``.
log_event_typeNoFilter to a specific event type.
sort_directionNo``asc`` or ``desc``.
max_date_createdNoLatest creation time, epoch microseconds.
min_date_createdNoEarliest creation time, epoch microseconds.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 burden. It only says 'Get logs' implying a read operation, but does not disclose pagination behavior, rate limits, data scope (e.g., per-app filtering beyond the required app_id), or whether logs are real-time or historical.

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 a single sentence, efficient and to the point, with no wasted words. It clearly communicates the core action, though it might benefit from slightly more context.

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?

Despite high schema coverage and an output schema, the description omits high-level context such as the purpose of filtering parameters (e.g., source, date range) and the nature of returned logs. A tool with 11 parameters deserves a description that summarizes key capabilities beyond the bare minimum.

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 description coverage is 100%, so the baseline is 3. The description adds no extra meaning; it simply states the tool's purpose without elaborating on any parameters.

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 retrieves logs for a specified workflow app, with a specific verb ('Get') and resource ('logs'), and distinguishes it from sibling tools like 'ai_apps_list' (which lists apps) and apps_manifest_* (which manage app manifests).

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternative logging or app-related tools. There is no mention of prerequisites, use cases, or comparisons with siblings.

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/karbassi/slack-mcp'

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