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KumoRFM MCP Server

KumoRFM MCP Server

Official
by kumo-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

🔍 Searching for tabular files…

find_table_files
Read-onlyIdempotent

Scans a local directory for table-like files (CSV, Parquet) and optionally includes subdirectories.

Instructions

Finds all table-like files (e.g., CSV, Parquet) in a directory.

This tool is for local directories only. It cannot search, e.g., in S3 buckets.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "find_table_files"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesLocal root directory to scan
recursiveNoWhether to scan subdirectories recursively. Use with caution in large directories such as home folders or system directories.

Output Schema

NameRequiredDescriptionDefault
resultYes

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?

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds behavioral context by specifying it searches locally and cannot access remote storage, which complements 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?

Two concise sentences: the first states the core purpose, the second clarifies scope. No redundant words, and the information is front-loaded for quick comprehension.

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?

Given the tool's simplicity (2 parameters, 1 required), the presence of an output schema, and the annotations, the description fully covers purpose, scope, and parameter hints without needing to explain return values or error behavior.

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?

The input schema already covers both parameters with descriptions. The description adds value by providing concrete file type examples (CSV, Parquet), which helps users understand what 'table-like' means, going beyond the schema's formal definitions.

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's function ('Finds all table-like files') with specific examples (CSV, Parquet), and distinguishes it from siblings like 'inspect_table_files' by focusing on discovery rather than inspection.

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?

The description explicitly limits usage to local directories and warns against using it for remote storage like S3. This provides clear when-to-use and when-not-to-use guidance, though it does not directly suggest alternative tools.

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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