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Glama

YouSpot

by com.youspot

List brain objects

list_graph_objects
Read-only

List objects in the user's graph, newest first, with counts by type. The graph is their personal CRM's object store: person, company, hubspot_contact, linkedin_connection, file, fact, web_link, note, connected spaces, and more. Filter by type to browse one kind ('what files do I have?', 'list my facts'), or omit it to see what the graph holds overall. For finding something by name, prefer search_graph_objects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOnly objects of this type (e.g. 'fact', 'web_link').
limitNoMax results (default 20, max 50).

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds meaningful behavior beyond that: newest-first ordering, counts by type, and the graph's role as a personal CRM object store. No contradiction with annotations, though it does not mention pagination or rate-limit behavior.

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?

Four sentences, all substantive, with the core behavior front-loaded before context and routing guidance. No filler or redundant restating of the schema.

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 read-only listing tool with two optional parameters and no output schema, this is nearly complete: purpose, ordering, counts, filtering behavior, allowed types, and an alternative are all covered. It could specify the exact shape of the returned counts, but nothing essential is missing for an agent to invoke it correctly.

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 the baseline is 3. The description adds value by giving concrete example values ('fact', 'web_link'), explaining the effect of omitting type, and tying the type parameter to user intents like 'what files do I have?' and 'list my facts.'

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?

States a concrete operation: list objects in the user's graph, with ordering ('newest first') and aggregate behavior ('counts by type'). Clearly distinguishes itself from sibling search_graph_objects by explicitly routing name-based lookups elsewhere, and from get_graph_object by being a list operation.

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

Usage Guidelines5/5

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

Provides direct when-to-use guidance: filter by type to browse one kind, omit type to see the whole graph. Explicitly names the preferred alternative for name-based search: 'For finding something by name, prefer search_graph_objects.'

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.

Resources