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Get brain object

get_graph_object
Read-only

Get one object from the user's graph, with the objects connected to it (its edges, e.g. a person's spaces, a note's subject). Identify it by object_id (exact, preferred — search and list return it) or by name. Use this when the user asks about a specific thing in their graph, or to follow a connection you found on another object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoThe object's name (full or partial).
object_idNoExact node id (e.g. web_aBc123), if known.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds useful behavioral context beyond that: the tool returns not only the requested object but also its connected objects/edges, and it supports lookup by either object_id or name. This gives the agent a clear expectation of what the call will return.

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 two sentences with no filler. The core behavior and return value are front-loaded, and the usage guidance follows naturally. Every clause earns its place.

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 read tool with two optional parameters and no output schema, the description provides enough context: what it retrieves, how to identify the object, and when to use it. A slightly more explicit note about ambiguous name matches or missing objects would push it to 5, but this is adequate for confident invocation.

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 is 100%, so both parameters are documented in the schema. The description adds meaningful semantics on top: object_id is exact and preferred, and search/list return it; name can be full or partial. This helps the agent choose the right parameter and understand matching behavior.

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 action ('Get one object'), the resource ('user's graph'), and the distinguishing feature (returns connected objects/edges). It names concrete examples (person's spaces, note's subject), which makes the tool's role unmistakable and differentiates it from searching or listing graph objects.

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 tells the agent when to use this tool: when the user asks about a specific thing in their graph, or when following a connection found on another object. It does not explicitly say when not to use alternatives like search_graph_objects or list_graph_objects, but the 'specific thing' guidance strongly implies the distinction.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools are scoped to a distinct resource and action, and descriptions do a good job separating close pairs like search_connections vs ask_about_connections or get_my_linkedin_posts vs linkedin_analytics. However, the multiple deletion tools (delete_graph_object, delete_graph_objects, purge_graph_object) and the several file-reading tools are easy to confuse without reading the descriptions carefully.

Naming Consistency4/5

The vast majority of tools follow a clear verb_noun pattern such as create_, get_, list_, search_, send_, and delete_. A handful of noun-phrase outliers like linkedin_analytics, mutual_connections, top_message_correspondents, and what_needs_attention break the pattern, so it is highly consistent but not perfect.

Tool Count1/5

64 tools is an extreme count, far beyond the typical well-scoped 3-15 tool range and even beyond the 25+ threshold for 'too many'. While the server covers many integrations, this many tools creates a heavy navigation burden and would be better split into focused servers per domain.

Completeness3/5

Core graph/CRM operations and read-side integration coverage are strong, with search, get, list, and create tools across most domains. However, there are notable dead ends: no delete_calendar_event, no tracker management beyond create_tracker, and set_follow_up explicitly lacks a read-back query tool, so some natural user requests cannot be completed through the toolset.