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csv-mcp

csv-mcp

by meysam-kazemi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

query_csv

Select, filter, and sort rows from a CSV file using controlled operators. Apply column selection, criteria filters, and sorting with configurable parsing options.

Instructions

Select, filter, and sort rows with controlled operators.

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": "query_csv"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
sortNo
limitNo
selectNo
filtersNo
optionsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations exist, so the description must convey behavioral traits. It does not state whether the tool is read-only, modifies the file, or has any side effects. 'Select, filter, and sort' implies querying but lacks explicit assurance of non-destructive behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, making it concise. However, it sacrifices substance for brevity, leaving out important details that could be included without much length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, nested objects, multiple operators), the description is incomplete. It does not explain the return format (though output schema exists), nor does it provide needed context about the 'controlled operators' or how to construct queries.

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

Parameters2/5

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

With 0% schema description coverage, the description must explain parameters. It mentions 'select, filter, and sort' which correspond to parameters 'select', 'filters', and 'sort', but provides no details on allowed operators, value formats, or how to use them. The schema itself lacks descriptions for individual parameters.

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 clearly states the tool performs select, filter, and sort operations on CSV rows, distinguishing it from sibling tools like read_csv (reading without filtering) or preview_csv (first few rows). The phrase 'controlled operators' is somewhat vague but acceptable.

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 versus alternatives. For example, it does not indicate that for simple reading, read_csv is sufficient, or that for aggregation, summarize_csv is appropriate. This omission is critical given the many sibling 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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