Skip to main content
Glama

session_start

Start or resume a session to retrieve standing context—goals, rules, preferences, and lessons—before beginning work.

Instructions

Start (or resume) a session. Returns standing context (goals, rules, preferences, lessons) to load before work.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetNo
session_idNo

Schema Changelog

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

  1. First observedv0.2.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does disclose that the tool starts or resumes a session and returns standing context, which is useful. But it does not mention side effects, persistence behavior, authentication requirements, or how dataset/session_id affect the operation.

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 short sentences with no filler. The primary action is front-loaded, and the return-value note is concise and informative.

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

Completeness2/5

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

The purpose is clear, but the description is incomplete for a tool with no annotations and no output schema. The missing explanation of dataset and session_id leaves a significant gap for correct invocation, especially for the 'resume' case. There is also no mention of what happens if no arguments are provided.

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

Parameters1/5

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

Schema description coverage is 0% and the description never mentions the two parameters, dataset and session_id. An agent cannot tell what these parameters mean, how they relate to starting versus resuming, or whether they are scoping or identification values. The description adds no parameter-level guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource: "Start (or resume) a session," and adds value by noting it returns standing context (goals, rules, preferences, lessons). It distinguishes itself from most siblings by focusing on session lifecycle initiation rather than retrieval or mutation, but it does not explicitly name or contrast any sibling tool.

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 phrase "to load before work" gives a clear usage context: this is the tool to call at the beginning of a work session or when resuming one. However, it does not explicitly state when not to use it or point to alternatives like session_get or session_timeline.

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

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/AndrewNgo-ini/mnemoth'

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