Hebbrix MCP Server

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hebbrix_search_entities

Read-onlyIdempotent

Retrieve people, organizations, tools, and places from the knowledge graph, with optional filtering by entity type, to answer who or what you know about.

Instructions

List entities in the knowledge graph (people, organizations, tools, places), optionally filtered by entity_type. Use for "who/what do I know about" questions.

Note: entities are enriched ASYNCHRONOUSLY after a write (not covered by hebbrix_remember's wait_for_index) — a just-written fact's entities typically appear here within ~30s, so an empty result right after a write is expected.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "hebbrix_search_entities"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`entity_type`	No
`collection_id`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.3Jul 9, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description discloses non-obvious behavior: entities are enriched asynchronously after a write, not covered by hebbrix_remember's wait_for_index, and may appear within ~30s. This explains why an empty result right after a write is expected, adding valuable context beyond the schema.

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 and well-structured: a clear purpose sentence with optional filter, followed by a relevant note about asynchronous behavior. Every sentence adds value and there is no redundant or filler content.

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?

The description covers purpose, usage, and the key behavioral caveat, while the output schema likely handles return-value details and annotations cover safety. However, collection_id remains unexplained, which is a minor gap for a tool that otherwise feels complete.

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

Parameters2/5

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

The schema has 0% description coverage for its parameters. The description clarifies only entity_type (as an optional filter with examples) but does not explain collection_id or limit. Since the description fails to compensate for the low schema coverage, especially for collection_id, the parameter semantics are insufficiently defined.

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 identifies the tool's action ('List') and resource ('entities in the knowledge graph'), with concrete examples of entity types (people, organizations, tools, places). It effectively distinguishes this tool from siblings like hebbrix_search or hebbrix_graph_query by focusing on entity listing for 'who/what do I know about' questions.

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?

The description explicitly gives usage context with 'Use for "who/what do I know about" questions' and provides a crucial caveat about asynchronous enrichment after writes. It does not name alternative tools or explicitly say when not to use it, but the guidance is clear enough for an agent to decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.