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sourav-spd

AWS S3 Connector MCP Server

by sourav-spd

Import CSV to Table

import_csv_to_table

Imports data from a CSV file in S3 into an S3 table, creating the table with schema inferred from the CSV if it doesn't exist.

Instructions

Reads data from a CSV file stored in S3 and imports it into an S3 table. If the table doesn't exist, it will be created with a schema inferred from the CSV.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uriYesREST URI for Iceberg catalog
regionYesAWS region for S3Tables/Iceberg REST endpoint
s3_urlYesThe S3 URL of the CSV file (format: s3://bucket-name/key)
namespaceYesThe namespace. Must be 1-255 characters long.
warehouseYesWarehouse string for Iceberg catalog
table_nameYesThe table name. Must be 1-255 characters long.
catalog_nameNoCatalog name
preserve_caseNoPreserve case of column names
rest_signing_nameNoREST signing name
rest_sigv4_enabledNoEnable SigV4 signing
Behavior3/5

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

With no annotations, the description carries full burden. It discloses schema inference on creation but omits whether data is appended or replaced if table exists. Adequate but incomplete.

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, front-loaded with action, no redundancy.

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?

For a tool with 10 parameters and no output schema, the description is too brief. Missing return info, behavior on existing tables, and handling of CSV format specifics.

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 baseline is 3. Description adds no extra detail about parameters like preserve_case or catalog_name beyond their schema descriptions.

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 imports CSV from S3 into an S3 table and creates the table with inferred schema if missing. This is a specific verb+resource description that distinguishes from siblings like import_parquet_to_table.

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 explicit guidance on when to use this tool versus alternatives (e.g., import_parquet_to_table, append_rows_to_table). No prerequisites or conditions mentioned.

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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