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MSSQL MCP Server

by EvilPhatBoi
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TypeScript
Hybrid

insert_data

Adds single or multiple records to MSSQL database tables using SQL INSERT statements with proper formatting for data types and column structures.

Instructions

Inserts data into an MSSQL Database table. Supports both single record insertion and multiple record insertion using standard SQL INSERT with VALUES clause. FORMAT EXAMPLES: Single Record Insert: { "tableName": "Users", "data": { "name": "John Doe", "email": "john@example.com", "age": 30, "isActive": true, "createdDate": "2023-01-15" } } Multiple Records Insert: { "tableName": "Users", "data": [ { "name": "John Doe", "email": "john@example.com", "age": 30, "isActive": true, "createdDate": "2023-01-15" }, { "name": "Jane Smith", "email": "jane@example.com", "age": 25, "isActive": false, "createdDate": "2023-01-16" } ] } GENERATED SQL FORMAT:

  • Single: INSERT INTO table (col1, col2) VALUES (@param1, @param2)

  • Multiple: INSERT INTO table (col1, col2) VALUES (@param1, @param2), (@param3, @param4), ... IMPORTANT RULES:

  • For single record: Use a single object for the 'data' field

  • For multiple records: Use an array of objects for the 'data' field

  • All objects in array must have identical column names

  • Column names must match the actual database table columns exactly

  • Values should match the expected data types (string, number, boolean, date)

  • Use proper date format for date columns (YYYY-MM-DD or ISO format)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNameYesName of the table to insert data into
dataYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing important behavioral traits: it explains the SQL generation format, specifies important rules about data structure consistency, column name matching, and data type requirements. It also clarifies the single vs. multiple record distinction. The main gap is lack of information about permissions, transaction behavior, or error handling.

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 well-structured with clear sections (purpose statement, format examples, generated SQL format, important rules). While comprehensive, it could be more concise by eliminating some redundancy between the format examples and rules. Every sentence adds value, but the examples are quite detailed.

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

Completeness4/5

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

For a mutation tool with no annotations and no output schema, the description provides substantial context about behavior, parameters, and constraints. It covers the core functionality thoroughly but lacks information about return values, error conditions, or performance characteristics. Given the complexity of database operations, some additional context about what happens on success/failure would be beneficial.

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?

The description adds significant value beyond the 50% schema coverage. While the schema only describes basic structure, the description provides detailed format examples for both single and multiple records, explains the 'data' field's dual nature with clear rules, specifies column name matching requirements, and provides data type guidance. This fully compensates for the schema's limited coverage.

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 specific action ('inserts data'), target resource ('MSSQL Database table'), and scope ('supports both single record insertion and multiple record insertion'). It distinguishes from siblings like 'update_data' by focusing on insertion rather than modification, and from 'create_table' by operating on existing tables rather than creating new ones.

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 provides clear context for when to use this tool (inserting data into tables) and implicitly distinguishes it from alternatives like 'update_data' (for modifying existing records) and 'create_table' (for creating table structures). However, it doesn't explicitly state when NOT to use this tool or name specific alternative tools for related operations.

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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