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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

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
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
memory_loadA

Load memory state for an agent. Call on resurrection/startup.

memory_saveA

Save current memory state to disk. Call before shutdown or periodically.

memory_add_messageB

Add a message to the memory buffer for later summarization.

memory_get_contextA

Get the full rendered context for injection into system prompt.

memory_get_laneB

Get messages from a lane for summarization by external LLM.

memory_apply_summaryB

Apply a lane summary (after LLM summarization).

memory_get_recentB

Get recent messages for persona mining/reflection.

memory_apply_personaC

Apply a persona update (from LLM persona mining).

memory_statusC

Get memory status: persona weights, lane sizes, token estimate.

memory_set_normativeC

Set the normative policy block (soft defaults, evolvable).

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.5/5.0

Scored across 10 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: load/save manage persistence, add_message feeds buffer, get_context renders full context, get_lane pulls from a lane, apply_summary writes summaries, get_recent fetches recent messages for persona, apply_persona updates persona, status reports health, and set_normative sets policy. No two tools appear to overlap in function.

Naming Consistency5/5

All tools follow the prefix memory_ followed by a descriptive verb (load, save, add_message, get_context, get_lane, apply_summary, get_recent, apply_persona, status, set_normative). The pattern is consistent, with the only minor deviation being 'status' (a noun) but this is a common exception and does not break the overall predictability.

Tool Count5/5

10 tools is well within the ideal range for a memory management server. Each tool addresses a specific lifecycle or action (persistence, message ingestion, context retrieval, summarization, persona, status, policy) without redundancy, making the set appropriately scoped.

Completeness4/5

The tool surface covers the core memory lifecycle: load/save, add messages, get context, manage lanes and summaries, handle personas, and set normative policy. Minor gaps exist, such as no explicit clear/delete operations or direct retrieval of a single message, but these are easily worked around and do not break typical workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues