Skip to main content
Glama

session_context

Read-only

Returns the token owner (signed-in user), the company and the language of its data, token scopes, the owner's privileges (allows) and token expiry (expiresAt; null - no expiry). Also includes the company's and user's conventions and notes for AI agents (memoryInstructions) with an index of further memory records (memory: ID → title), as reference material. Also returns the company's, user's and token's variables for AI agents (variables): description, file path (file) or environment variable name (env), and the value of short non-secret environment variables only. In work on a task, the variables of the product context apply.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description still adds real behavioral context: expiresAt can be null (no expiry), and only 'short non-secret environment variables' have their values exposed, which is a meaningful disclosure about what is and is not returned. It stops short of describing freshness, caching, or cost.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The content is dense and mostly earns its place, but it is delivered as long run-on sentences that stack clause after clause ('Also... Also...') with no structure. Front-loading is adequate — the primary return set leads — but a bulleted breakdown of the three return groups would be far more scannable.

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?

With no output schema, the description carries the full burden of explaining returns, and it does so thoroughly, covering identity, scopes, privileges, expiry, memory index, and variables. What it omits is routing context relative to the many sibling context tools, which an agent in this dense tool namespace would need.

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 tool takes zero parameters, so per the rubric the baseline is 4. The description correctly adds no parameter noise and instead spends its words on return content.

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 states a specific resource (session/token context) and enumerates the exact fields returned: token owner, company, language, scopes, privileges, expiry, memory index, and variables. An agent knows precisely what this tool yields. It never distinguishes itself from sibling context tools such as product_context, task_context, or repo_context, so it stops short of a 5.

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

Usage Guidelines2/5

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

There is no statement of when to call this versus the many sibling context tools (product_context, task_context, repo_context, memory_list). The trailing sentence 'In work on a task, the variables of the product context apply' gestures at context layering but does not tell the agent when this tool is the right choice or what prerequisites exist.

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.

Resources