Skip to main content
Glama

YouSpot

Log interaction

record_interaction

Record one dated touchpoint with someone in the user's graph — an email exchanged, a call, a meeting, a LinkedIn touch, or a manually noted contact — so 'when did I last talk to them?' has an answer. Creates an interaction object connected to the person it happened with; get with_object_id from search_graph_objects. occurred_at is ISO 8601 ('2026-08-28T15:00:00Z') and may be in the future ('we're meeting next Tuesday'). direction is from the user's point of view: inbound means they reached out to the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelYesHow it happened.
summaryYesOne or two sentences on what happened.
directionYes'inbound' when they contacted the user, 'outbound' when the user reached out.
occurred_atYesWhen it happened (ISO 8601; future is fine).
with_object_idYesWho it happened with (their exact object_id).

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations only mark readOnlyHint=false, so the description adds value by stating that a new interaction object is created and connected to the person. It also discloses that future timestamps are acceptable and that the person must already be a graph object. It does not cover failure modes or duplicate interactions, but this is adequate for a simple create action.

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?

Three sentences, each with a distinct job: scope and purpose, object creation and prerequisite, parameter semantics. There is no filler and no mere repetition of schema text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with five required parameters and no output schema, the description covers all the non-obvious information an agent needs: input types, date syntax, direction interpretation, and where to obtain the person's ID. No critical usage gap remains.

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?

The input schema already documents all five parameters, so the baseline is 3. The description adds real meaning for three of them: occurred_at format and future dates, direction from the user's point of view, and the source of with_object_id. Channel and summary are self-explanatory and need no extra detail.

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 opens with a specific verb ('record'), defines the resource ('one dated touchpoint' / 'interaction object'), and enumerates accepted interaction types. It makes clear that the tool creates an interaction object connected to an existing person, which distinguishes it from generic graph creation tools.

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?

It gives a clear purpose — answering 'when did I last talk to them?' — and a concrete prerequisite: get with_object_id from search_graph_objects. It does not explicitly name alternatives or state when not to use the tool, so it stops just short of full guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.