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tibero-mcp

tibero-mcp

by jdk1021
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

query

Read-only

Execute read-only SELECT or WITH statements against Tibero with bind parameters and row caps; returns columns, rows, and pagination info for paging truncated results.

Instructions

Run a read-only query and return columns and rows. truncated is true when more rows exist.

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": {
      "sql": "<sql>"
    },
    "name": "query"
  }
}

Input Schema

NameRequiredDescriptionDefault
sqlYesOne SELECT or WITH statement. Use ? placeholders for values.
offsetNoRows to skip; pass next_offset from a truncated result to page.
paramsNoValues bound to ? placeholders, in order.
max_rowsNoRow cap for this call (server maximum 500).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

The readOnlyHint annotation already establishes the safety profile, so the description's remaining job is smaller. It does add the pagination signal ('truncated' is true when more rows exist), which is genuinely useful for driving the offset parameter, but says nothing about statement restrictions, timeouts, or error behavior.

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 short sentences, no filler, and the capability is front-loaded before the pagination detail. Nothing is padded or restated from the title.

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?

An output schema exists, so the description needn't enumerate return fields, and all four parameters are fully documented. What remains thin is only failure modes and the single-statement constraint (documented in the schema but not the description), which is a minor gap for an otherwise well-covered tool.

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

Parameters4/5

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

With schema coverage at 100%, the schema already defines sql, offset, params and max_rows including the ? placeholder convention and the 500-row ceiling. The description adds the operational link between 'truncated' and the offset parameter, which goes slightly beyond the schema and is the one cross-parameter behavior the schema cannot express.

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 names a specific verb+resource pair ('Run a read-only query') and states what comes back ('columns and rows'), so the agent knows it is the data-fetching tool rather than a metadata one. It does not distinguish itself from the sibling 'explain', which plausibly also accepts SQL and could be confused with it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied by the phrase 'read-only query' — the agent can infer you use this to retrieve data. There is no explicit statement of when to prefer this over list_tables/describe_table for schema discovery, and no note on when 'explain' would be the better choice.

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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