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Glama
Thanatos9404

llmslim

by Thanatos9404
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LLMSLIM_USER_IDNoWhose memory this server holds. The server fixes this scope, so the model cannot read another user's memory. Default: default
LLMSLIM_AGENT_IDNoOptional agent id, so each agent keeps its own memory.
LLMSLIM_MEMORY_DBNoSQLite file or postgresql:// URL for the memory. Default: ~/.llmslim/memory.db

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": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}

Tools

Functions exposed to the LLM to take actions

NameDescription
rememberA

Store a message in long-term memory, word for word.

    Args:
        text: The message to keep, in the speaker's own words.
        role: Who said it: "user" (default) or "assistant".
        session: Optional id of the conversation it belongs to. Messages without one are grouped by day.
recallA

Find what earlier conversations said about a question: the stored messages that answer it, whole and under their dates, within a token budget.

    Args:
        query: The question, e.g. the user's latest message.
        budget: Most tokens to return. Defaults to the server's budget.
        session: Optional conversation id to search only that conversation.
list_memoriesA

List the most recently stored messages with their ids, newest first.

    Args:
        limit: How many to list, at most 100.
        session: Optional conversation id to list only that conversation.
forgetA

Delete one stored message by its id (from remember or list_memories). This cannot be undone.

    Args:
        memory_id: The id of the message to delete.
fit_contextA

Shrink a long text (a document, log or tool output) to a token budget, keeping the parts that answer the query, in their original order. Text that already fits comes back unchanged.

    Args:
        text: The text to shrink.
        budget: Most tokens to return.
        query: Optional question; the parts that answer it are kept first.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

TDQS

A3.9/5.0

Scored across 5 tools

Disambiguation4/5

Each tool targets a distinct operation: remember stores, list_memories lists recent ids, recall searches by query, forget deletes by id, and fit_context compresses arbitrary text. Minimal overlap exists (recall/list_memories both surface stored messages; recall/fit_context both use query+budget), but descriptions clarify boundaries.

Naming Consistency4/5

All names use lowercase snake_case, but the pattern mixes single verbs (recall, remember, forget) with verb_noun compounds (list_memories, fit_context). This is still readable and largely predictable, with only minor inconsistency.

Tool Count5/5

Five tools is well-scoped for a memory/context server. Each tool earns its place: store, list, search, delete, and compress, with no redundant or missing core operations.

Completeness4/5

Core memory lifecycle is covered: create (remember), read/list/search (list_memories, recall), delete (forget), plus fit_context. Minor gaps exist: no direct get_memory by id and no update (though messages are immutable), which may force workarounds for id-based retrieval.

Maintenance

ActivityActive
ResponsivenessSlow

Resources