dakera-mcp

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dakera_hybrid_search

Combine BM25 keyword and vector ANN semantic search in a single query. Adjust vector weight to balance between keyword-only and semantic-only retrieval, ideal for RAG when either alone falls short.

Instructions

BM25 + vector ANN hybrid search in a single pass. Omit vector for BM25-only mode. Use for RAG when pure semantic or keyword search alone is insufficient. vector_weight: 0.0=BM25, 1.0=vector (default 0.5).

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": {
      "namespace": "<namespace>",
      "text": "<text>"
    },
    "name": "dakera_hybrid_search"
  }
}

Input Schema

Name	Required	Description
`text`	Yes	Text query for full-text search
`top_k`	No	Number of results to return
`filter`	No	Optional metadata filter
`vector`	No	Query embedding; omit for BM25-only.
`namespace`	Yes	Namespace to search in
`vector_weight`	No	Vector score weight 0.0–1.0; text weight = 1−value.
`include_vectors`	No
`include_metadata`	No

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.10.8May 21, 2026

TDQS

A4.1/5.0

Behavior3/5

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

With no annotations, the description explains the hybrid algorithm and weight behavior, but does not disclose safety, permissions, cost, or error behavior. The 'single pass' note gives a performance hint, but overall transparency is limited.

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, front-loaded sentences with no redundancy. Every sentence provides essential information, and the structure is clear.

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?

Given 8 parameters, nested filter object, and no output schema, the description is somewhat minimal. It does not explain return values, pagination, or results handling, leaving gaps for a complex search 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?

Schema coverage is 75% (two parameters lack descriptions in schema). The description adds meaning by explaining the vector parameter for BM25-only mode and the vector_weight range, enhancing understanding beyond the schema.

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 specifies a hybrid search combining BM25 and vector ANN in a single pass, and distinguishes from siblings by noting BM25-only mode and use case for RAG when pure methods are insufficient.

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?

Explicitly states when to use ('RAG when pure semantic or keyword search alone is insufficient') and how to configure modes (omit vector for BM25-only, adjust vector_weight). Lacks explicit exclusion criteria but provides clear context.

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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