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Mnemosyne MCP

Mnemosyne MCP

by zhadyz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

read_graph

Access the full knowledge graph memory to retrieve all stored facts and relationships for AI agents.

Instructions

Read the entire Memento MCP knowledge graph memory system

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": "read_graph"
  }
}

Input Schema

NameRequiredDescriptionDefault
random_stringNoDummy parameter for no-parameter tools

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.2

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are present, so the description carries the burden. 'Read' communicates a non-destructive operation and 'entire' indicates broad scope, but it does not disclose potential performance costs, response size, or exact return format, leaving some behavioral ambiguity.

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 a single, clear sentence that is front-loaded with the action and resource. Every word contributes to the meaning, with no redundancy or filler.

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?

For a simple, no-required-parameter graph read operation, the description adequately states scope and intent. The lack of an output schema is acceptable given the straightforward 'read entire graph' semantics, though a note on return format would make it slightly more 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?

The schema fully describes the lone dummy parameter with 100% coverage, and the description adds no parameter-specific information. A baseline of 3 is appropriate because the schema already handles parameter semantics.

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 uses the specific verb 'Read' and identifies the resource as the 'entire Memento MCP knowledge graph memory system', making the tool's scope explicit. It clearly distinguishes this from sibling tools like search_nodes and get_graph_at_time, which imply filtered or temporal subsets.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives. It does not mention that search_nodes or get_graph_at_time could be better for specific queries, nor does it state exclusions such as 'use only when you need the full graph'.

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

Deploy Server

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