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bpamiri

SQL Server MCP

by bpamiri

save_knowledge

Persist discovered knowledge about an SQL Server database schema, table structures, query patterns, and data meanings for use in future conversations.

Instructions

Save learned information about the SQL Server database.

Use this to persist useful discoveries about the database schema,
table structures, query patterns, and data meanings. This information
will be available in future conversations.

Good things to save:
- Table purposes (e.g., "Customers contains customer master records")
- Column meanings (e.g., "In Orders, StatusCode 1=Pending, 2=Shipped")
- Working query patterns that produced good results
- Relationships between tables (foreign keys, joins)
- Data format notes (date formats, codes, etc.)
- Stored procedure documentation

Args:
    topic: A short descriptive name for this knowledge
           (e.g., "Customers table", "Order queries", "Status codes")
    content: The knowledge to save. Use markdown formatting.
    append: If True, add to existing topic. If False, replace it.

Returns:
    Status of the save operation.

Examples:
    save_knowledge("dbo.Customers", "Customer master table. PK is CustomerID.")
    save_knowledge("Date formats", "Dates stored as datetime2. Use FORMAT() for display.")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
appendNo
contentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Despite no annotations, description discloses key behaviors: persistence across conversations, append vs replace mode, and return status. It does not mention any destructive side effects or required permissions, but the tool appears safe.

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?

Well-structured with introductory sentence, bullet list of use cases, clear parameter descriptions, return type, and two examples. No superfluous information.

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, the presence of an output schema, and no annotations, the description covers all necessary aspects: purpose, usage, parameters, return value, and examples. Fully complete.

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?

Schema coverage is 0% (no descriptions in schema), but description provides detailed explanations for all three parameters including default behavior and format hints. Examples further clarify usage.

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?

Description explicitly states 'Save learned information about the SQL Server database', using a specific verb and resource. It clearly distinguishes from sibling tools like list_knowledge, get_knowledge_topic, and search_knowledge.

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?

Provides explicit guidance on when to use the tool, with a list of 'Good things to save' giving concrete examples. Does not explicitly mention alternatives or when not to use, but the context is clear enough.

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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