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Laminar Agent

AI agent

by Laminar

Laminar Agent answers questions about project data by querying it directly.

Find alternatives to Laminar Agent

What it does

• Data analysis

Features 6

• Slack integrationMention @Laminar in a connected channel and the agent replies in the thread.
• MCP server ask_agent toolAsk the agent from Claude Code, Cursor or Codex with the ask_agent tool.
• CLI ask commandAsk the agent from the terminal with lmnr-cli ask, continuing a conversation with a conversation id.
• Run SQLWrites and runs read-only ClickHouse SELECT queries across traces, spans, signal events, clusters, evaluations and tags.
• Read a tracePulls a compact view of the full span structure to explain, summarize or debug a specific run.
• Search inside a traceFuzzy-matches a string across one trace's span inputs and outputs and returns snippets with context.

Sources

Pricing

Pricing page · 15 Oct 2026

"3 GB data included"

Description

Official documentation · 15 Oct 2026

"answers questions about your data by querying it directly."

What it does

Official documentation · 15 Oct 2026

"It runs read-only SQL and reads trace context for you"

Sold within

Official documentation · 15 Oct 2026

"that lives inside your project"

Name

Official documentation · 15 Oct 2026

"Laminar Agent is an AI agent"

URL

Official documentation · 15 Oct 2026

"Laminar Agent is an AI agent"

Deployment

Official documentation · 15 Oct 2026

"Laminar Cloud: the fully managed service at laminar.sh."

Interfaces

Official documentation · 18 Oct 2026

Page: 'Slack Mention @Laminar in a connected channel and it replies in the thread. MCP server Ask the agent from Claude Code, Cursor, or Codex with the ask_agent tool. CLI Ask the agent from your terminal with lmnr-cli ask'.

Also from Laminar

• Laminar Signals Developer tool

  Laminar Signals uses a trace analysis agent to identify AI agent failures and produce structured events for monitoring and alerts.

• Laminar Infrastructure service

  Open-source observability platform for AI agents: captures traces of LLM and tool calls, analyzes every run for failures with its flow-1 model, and adds evaluations, an agent debugger, labeling queues, dashboards and SQL access, on Laminar Cloud or self-hosted.

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