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lynx-mcp

by lorenzo-cambiaghi
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Python
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list_sources

Read-onlyIdempotent

List available sources with their name, type, path, chunk count, and drift flag. Use to identify valid source names before querying or managing them.

Instructions

List which sources exist and what each one is: name, type, path, chunk count and drift flag. Read from config and metadata, no index opened. Call it first when you do not know the source names a source argument expects; for how fresh one index is, and whether to rebuild it, use get_rag_status instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.9.0
    • removedInput schema / title
      Removed value: -"list_sourcesArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "title": "Result",
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "list_sourcesOutput",
-  "type": "object"
-}New value: +null
  2. First observedv1.5.1

TDQS

A5/5.0
Behavior5/5

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

The description states 'Read from config and metadata, no index opened', which transparently explains that the operation is read-only and does not affect the index. This aligns with the annotations (readOnlyHint, idempotentHint, non-destructive) and provides extra context beyond the annotations.

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?

The description is concise and well-structured. It lists the returned fields in a compact list and provides usage guidance without unnecessary verbosity.

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?

The description fully explains what the tool does, what information it returns, and when to use it. It also references the related tool get_rag_status to guide the agent to alternative actions when needed, making the context complete.

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

Parameters5/5

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

There are no parameters, and the description makes it clear that the tool simply lists all sources without needing any input. No explanation of parameters is required.

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 lists existing sources and details what each source contains (name, type, path, chunk count, drift flag). It is unambiguous about the resource and the action.

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

Usage Guidelines5/5

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

The description explicitly tells when to use this tool: 'Call it first when you do not know the source names a `source` argument expects'. It also distinguishes it from get_rag_status, which should be used for freshness/rebuild checks.

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

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