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dakera-mcp

dakera-mcp

Official
by Dakera-AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Rust
Remote

dakera_fulltext_search

Search indexed documents with BM25 to retrieve exact-term matches for error codes, IDs, and names, ensuring precise recall when vector search is insufficient.

Instructions

BM25 keyword search over indexed documents. Use over vector search when exact-term recall matters (error codes, IDs, names). For semantic+keyword combined use dakera_hybrid_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": {
      "namespace": "<namespace>",
      "query": "<query>"
    },
    "name": "dakera_fulltext_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesSearch query text
top_kNoNumber of results to return
filterNoOptional metadata filter
namespaceYesNamespace to search in

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.10.12
  2. Removedv0.10.11
  3. Addedv0.10.8

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description must convey behavioral traits. 'Search' implies a read-only operation with no side effects, and the description does not hint at any modifications. However, it does not explicitly state that no data is altered, so a minor gap exists.

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?

The description is compact, using two sentences to convey purpose and usage guidance without unnecessary verbiage. It is well-structured and front-loads the core function.

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?

No output schema exists, so the description need not explain return values. It fully covers the tool's purpose, selection criteria, and relationship to sibling tools, leaving no critical information missing for an agent to use it correctly.

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?

All four parameters (query, top_k, filter, namespace) have descriptions in the schema, giving high coverage. The tool description adds no extra parameter-specific insights, so the baseline of 3 is appropriate.

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 tool performs 'BM25 keyword search over indexed documents' and explicitly distinguishes it from vector and hybrid search alternatives. It identifies the specific resource (indexed documents) and the verb (search) without ambiguity.

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

Usage Guidelines5/5

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

The description provides direct usage guidance: 'Use over vector search when exact-term recall matters' and 'For semantic+keyword combined use dakera_hybrid_search.' This tells the agent exactly when to select this tool over its siblings.

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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