Skip to main content
Glama
itachiuchihadev

Seq MCP Server

seq_query

Run analytical SQL-like queries against Seq log data to count, filter, group, and analyze events by time, level, message, signal, or date range.

Instructions

Execute an analytical SQL-like query against Seq log data (e.g., "select count(*) from stream group by time(5m)", "select @Timestamp, @Message, @Level from stream where @Level = 'Error' limit 50").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSeq SQL query to execute.
signalIdNoOptional signal ID to scope query.
toDateUtcNoOptional end time boundary in ISO 8601 format.
workspaceNoOptional workspace identifier.
fromDateUtcNoOptional start time boundary in ISO 8601 format.
timeoutSecondsNoTimeout in seconds for the query.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It implies a read/analytic operation but does not disclose whether it mutates state, permission requirements, rate limits, result-set limits, or how large-volume queries behave.

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?

A single front-loaded sentence with the verb and resource first, followed by two illustrative examples. It is slightly long, and the second example is arguably redundant, but nothing is wasted.

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

Completeness3/5

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

There is no output schema and no annotations, so the description should carry more: it says nothing about the shape of results, result-size limits, or the read-only nature. For an analytical query tool with six parameters, this leaves gaps an agent would want filled.

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%, so the schema already documents all six parameters, setting the baseline at 3. The description's example queries add some syntax flavor for the 'query' param but clarify nothing about signalId, workspace, time bounds, or timeout.

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 specific verb ('Execute') and resource ('analytical SQL-like query against Seq log data') and gives concrete query examples. However, it never distinguishes from the sibling seq_search, which also operates on log data, so an agent cannot tell them apart without opening schemas.

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?

The description offers example queries but no guidance on when to choose this tool over seq_search or seq_tail_events, nor any prerequisites. The examples illustrate query syntax rather than usage conditions.

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