Lancelot

lancedb_search

Search LanceDB for relevant documents using vector or text search

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

Input Schema

Name	Required	Description	Default
`limit`	No	Maximum number of results (default: the configured limit, 20; at most 200)
`query`	Yes	Search query string
`table`	No	Table to search (default: the configured table)
`searchType`	No	vector uses OpenAI embeddings, text matches words in the text column, auto uses vector when a key is set and text otherwise	auto
`textColumn`	No	Column holding the text
`vectorColumn`	No	Column holding the vectors

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 31, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are present, so the description carries the full behavioral burden, yet it says nothing about read-only safety, permissions, embedding/key requirements, or result shape. It only restates the search modes that the schema already documents in detail.

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?

A single front-loaded sentence with no filler. It is efficient, though the 'vector or text search' clause largely duplicates the searchType parameter documentation.

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

Completeness3/5

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

The fully documented schema covers the parameters, and no output schema exists so return values need not be explained. Still, with zero annotations and three sibling tools, the description should at minimum state that this is a read-only retrieval operation and how it differs from lancedb_query.

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 description coverage is 100%, with enum values, defaults, and the auto-mode logic all documented in the schema itself. The description adds nothing beyond that baseline, so a 3 is appropriate.

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?

States a specific verb and resource ('Search LanceDB for relevant documents') plus the two search modes, so the core operation is unambiguous. It does not distinguish itself from the sibling lancedb_query, leaving the agent to guess which retrieval tool to pick.

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 on when to use this versus lancedb_query, or when vector vs text mode is preferable beyond the schema's own explanation. The agent is given a capability but no selection rule.

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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