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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OPENAI_API_KEYNoOpenAI API key for summarization (optional, can be passed as tool parameter)

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
trim_messagesA

Compress chat message history using token-based trimming strategy. Removes oldest non-system messages when token count exceeds threshold while preserving system messages and recent context.

summarize_messagesA

Compress chat message history using AI-powered summarization strategy. Creates concise summaries of older messages while preserving system messages and recent context.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.9/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: summarize_messages uses AI-powered summarization to compress history by creating concise summaries, while trim_messages uses token-based trimming to remove oldest messages when exceeding thresholds. There is no overlap in their approaches, making them easily distinguishable.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern with underscore separation: summarize_messages and trim_messages. The naming is predictable and readable, with no deviations in style or convention.

Tool Count3/5

With only 2 tools, the server feels thin for a context management domain, as it lacks operations like retrieval, update, or deletion of summaries/trims. However, the tools cover compression strategies adequately for a minimal scope.

Completeness2/5

The server is severely incomplete for context management; it only offers compression methods (summarization and trimming) but lacks any tools to retrieve, modify, or manage the compressed contexts, leaving agents with no way to access or update the results of these operations.

Maintenance

ActivityInactive
ResponsivenessNo issues