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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
CORTEXMEM_MODELNoModel identifier used for compactionclaude-haiku-4-5-20251001
ANTHROPIC_API_KEYNoOptional API key to enable LLM-based session compaction via summarize_session
CORTEXMEM_MAX_TOKENSNoDefault maximum tokens for get_context3000

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
save_contextA

Save context to persistent memory. Call this whenever you make a decision, discover something non-obvious about the codebase, agree on a constraint with the user, note WIP state, or learn a coding preference. Saved context persists across sessions and editors. Call proactively — future sessions depend on what you save now.

get_contextA

Retrieve persistent memory from previous sessions. Call at session start with no arguments to get the context pyramid: project overview, current branch summary, and recent session summaries — all in ~500-800 tokens. Use with a query to do hierarchical search: matches project → branch → session summaries first, then drills into raw chunks only when needed. Use depth to control how deep to search. Always call this first in a new session.

summarize_sessionA

Compact and persist session memory into the context pyramid. Creates a session summary from saved context, rolls it up into a branch summary, then updates the project overview. Call at end of session. Works best with ANTHROPIC_API_KEY for LLM-powered compaction; falls back to deterministic summarization without it.

get_statusB

Quick stats on cortexmem: total chunks stored, breakdown by type, storage location, last init time, last indexed commit.

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 4 tools

Disambiguation4/5

Each tool targets a distinct phase of the memory lifecycle: save_context writes raw chunks, get_context reads/search, summarize_session compacts, and get_status reports stats. The only mild overlap is that both save_context and summarize_session persist data, but the descriptions clearly differentiate raw chunks from session summaries.

Naming Consistency5/5

All tool names use a consistent snake_case verb_noun pattern: save_context, get_status, get_context, summarize_session. The verbs (save, get, summarize) are standard and predictable.

Tool Count5/5

Four tools is a well-scoped, minimal set for a persistent memory server. Each tool maps to a distinct operation (write, read, summarize, status), and none feels redundant or missing at the count level.

Completeness4/5

The surface covers saving, retrieving, summarizing, and status reporting for persistent memory. However, it lacks an explicit delete/forget or edit operation, so agents cannot easily prune stale or incorrect memories — a minor but real gap.

Maintenance

ActivityInactive
ResponsivenessNo issues