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usecortex

Hydra DB MCP Server

by usecortex

Search Hydra DB Memory (deprecated)

hydra_db_search
Read-onlyIdempotent

Search stored agentic memories for relevant chunks with graph-enriched context, using fast semantic search or deeper graph traversal for personalized recall.

Instructions

DEPRECATED — use hydradb_query instead. Search through Hydra DB State-of-the-art agentic memories. Returns relevant chunks with graph-enriched context including entity paths and knowledge graph relations. Use this to find previously stored information, past conversations, user preferences, or any knowledge that has been ingested into Hydra DB memory. Supports both fast semantic search and deeper thinking mode with graph traversal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoRecall mode: 'fast' for quick semantic search, 'thinking' for deeper personalised recall with graph traversal (default: 'thinking')
queryYesThe search query to find relevant memories
max_resultsNoMaximum number of memory chunks to return (1-50, default: 10)
graph_contextNoWhether to include knowledge graph relations in results (default: true)
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable behavioral context: returns chunks with graph-enriched context, supports two modes with different graph traversal behavior. No contradiction with annotations.

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 three sentences, front-loaded with the most critical information (deprecation). Every sentence earns its place: deprecation notice, what it does and returns, and use cases with mode choices. No unnecessary words.

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?

Given no output schema, the description explains return format (chunks with graph context) and mentions use cases. It covers modes, deprecation, and replacement. Lacks details on pagination or empty results, but the deprecation context makes it sufficiently complete.

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%, so baseline 3. The description does not add significant new meaning beyond what the schema descriptions already provide for 'mode', 'query', 'max_results', and 'graph_context'. It repeats the mode options but not in more detail.

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 it searches Hydra DB memories and returns relevant chunks with graph-enriched context. It explicitly distinguishes from siblings by noting deprecation and pointing to hydradb_query as replacement. The verb 'Search through' and resource 'Hydra DB State-of-the-art agentic memories' are specific.

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 starts with 'DEPRECATED — use `hydradb_query` instead', providing explicit when-not and alternative usage. It also describes the two modes (fast/thinking) and their use cases, giving clear context for when to use each mode.

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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