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mem0-mcp

mem0-mcp

Official
by tensakulabs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

search_graph

Search the knowledge graph for entities and their relationships. Discover connections between people, projects, and concepts.

Instructions

Search the knowledge graph for entity relationships.

Finds entities matching the query and their connections.
Use this to understand relationships between people, projects,
technologies, and concepts.

Args:
    query: Entity or topic to search for (e.g., "Justin", "OpenClaw",
           "Hetzner server")

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": {
      "query": "<query>"
    },
    "name": "search_graph"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior3/5

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

Without annotations, the description carries the burden of disclosing behavior. It states what the tool does (search and find connections) but does not describe limits, error handling, or behavior with no results. Moderate transparency.

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 brief (three sentences plus an Args section) with no fluff. It front-loads the main purpose and is well-structured.

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?

With one parameter and an existing output schema, the description is mostly complete: it explains input and output (entity relationships). It could add info on result format, but the output schema covers that.

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

Parameters4/5

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

Schema coverage for the 'query' parameter is 0%, but the description adds meaning: 'Entity or topic to search for' with examples. This effectively explains the parameter's purpose beyond the schema name.

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 searches a knowledge graph for entity relationships, with specific examples like 'Justin' and 'OpenClaw'. It distinguishes itself from the sibling 'search_memories' by focusing on relationships between entities.

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 advises using the tool to understand relationships among people, projects, etc., and provides example queries. However, it does not explicitly contrast with 'search_memories' or state when not to use it.

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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