Skip to main content
Glama
Sign In
Mnemograph

Mnemograph

by tm42
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

suggest_relations

Identify potential connections for an entity using semantic similarity and co-occurrence patterns. Helps link new entities or reveal missing relationships in your knowledge graph.

Instructions

Suggest potential relations for an entity based on semantic similarity and co-occurrence. Useful for connecting newly created entities or discovering missing links.

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": {
      "entity": "<entity>"
    },
    "name": "suggest_relations"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax suggestions to return
entityYesEntity name to get relation suggestions for

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions semantic similarity and co-occurrence but does not state whether the tool is read-only, if it modifies state, or any auth requirements.

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 sentences, no superfluous words, front-loaded with purpose. Every sentence adds value.

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?

Adequate for a simple suggestion tool with two parameters. No output schema is provided, but the description implies the return type. Could be more complete regarding output format.

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 coverage is 100%, both parameters have clear descriptions. The tool description adds no additional meaning beyond what the schema already provides, so baseline 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's verb ('suggest') and resource ('potential relations for an entity'), and distinguishes it from siblings like create_relations (which creates) and find_similar (which finds similar entities).

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

Usage Guidelines3/5

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

The description gives a use case ('connecting newly created entities or discovering missing links') but does not explicitly state when not to use it or name alternatives among the many sibling tools.

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

Deploy Server

Other Tools