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oh-my-mcp

oh-my-mcp

by quyansiyuanwang
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

parse_csv

Parse CSV strings into JSON objects. Specify delimiter to handle different formats.

Instructions

Parse CSV data and return as JSON.

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": {
      "csv_string": "<csv_string>"
    },
    "name": "parse_csv"
  }
}

Input Schema

NameRequiredDescriptionDefault
csv_stringYesCSV string to parse
delimiterNoCSV delimiter (default: ,),

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

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 must disclose behavioral traits. It only states parsing and JSON output, omitting details like header handling, error behavior, or output structure. The presence of an output schema is not leveraged in the description.

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?

The description is a single clear sentence, concise and without redundancy. It earns its place but could be slightly more structured with additional context.

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?

Given the simplicity (2 parameters, output schema exists), the description is minimally adequate. However, it lacks information on output format, error handling, and encoding, which would improve completeness.

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 input schema already documents both parameters. The description adds no extra meaning, examples, or constraints beyond what is in the schema.

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?

The description 'Parse CSV data and return as JSON' clearly states the verb, resource, and output format. However, it does not distinguish itself from the sibling tool 'csv_to_json', which likely has an identical purpose.

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?

No guidance is provided on when to use this tool vs alternatives like 'csv_to_json'. There is no mention of prerequisites, restrictions, or usage context.

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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