Skip to main content
Glama

read_graph

Retrieve paginated entities and relations from the knowledge graph. Returns total count and indicators for more data.

Instructions

Read the full knowledge graph with pagination.

Returns JSON: {entities: [{name, entityType, observations: [...]}], relations: [{from, to, relationType}], total: int, has_more: bool}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offsetNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description discloses the return format (JSON with entities, relations, total, has_more) and pagination behavior, but does not mention auth, rate limits, or performance characteristics.

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 succinct sentences with front-loaded purpose. Every word adds value.

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?

Output schema exists, and description adequately explains the return structure. However, it lacks explanation of how to use pagination parameters or when to use this vs sibling read tools.

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?

Schema coverage is 0%, and the description only mentions 'pagination' without explaining that offset and limit control pagination. Parameter meaning is left to inference from names and defaults.

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 reads the full knowledge graph with pagination, distinguishing it from mutation siblings like create_entities and delete_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 implies usage for reading, but does not explicitly differentiate from alternative read tools like search_nodes or open_nodes. No when-to-use or when-not-to-use guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/RMANOV/sqlite-memory-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server