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chacharin

mcp-lightrag

by chacharin

get_pipeline_status

Check LightRAG's indexing pipeline status to see if it is busy or idle, view current job name and progress, and read recent status messages for quick updates.

Instructions

Check what LightRAG's indexing pipeline is doing right now: busy or idle, current job name and progress, and the most recent status messages. Use this for "what is LightRAG processing" -- by default returns a short summary (the last 10 history lines), not the full internal state; pass verbose=true only if the summary is not enough.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
verboseNoReturn the full raw pipeline status (can be tens of kilobytes on a busy instance) instead of the condensed summary.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses that by default only a short summary of the last 10 history lines is returned, not full internal state, and that verbose returns raw full status that can be tens of kilobytes. This gives an agent important expectations about cost and output size.

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 sentences with no wasted words: the first states the resource and what the tool reports, the second immediately gives the default behavior and the condition for changing it. Every clause 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 simple read-only status tool with a single optional parameter and an output schema, the description is complete. It covers default behavior, verbose alternative, size caution, and the type of information returned, so an agent can invoke it correctly without further clarification.

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

Parameters4/5

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

Schema coverage for the single verbose parameter is 100% and the schema description already explains the condensed-vs-full distinction. The description adds value beyond the schema by instructing when to use verbose (only if summary is not enough) and warning about the potentially large response, which helps an agent decide parameter choice.

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?

Description names a specific resource (LightRAG's indexing pipeline) and verb (check), and enumerates exact outputs: busy/idle, job name, progress, recent status messages. It also frames the query 'what is LightRAG processing', which separates it from sibling status tools like get_scan_status and get_track_status.

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?

Explicitly says to use this for 'what is LightRAG processing' and instructs that verbose=true should be used only when the summary is not enough. It does not explicitly name sibling alternatives or say when another status tool should be preferred, so exclusions are missing.

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