Skip to main content
Glama
Master0fFate

LatentContext MCP Server

by Master0fFate

memory_retrieve

Retrieve memories stored in the current session to recall decisions and context, ensuring no cross-session data contamination.

Instructions

Retrieve memories stored in the CURRENT session. Returns only data from this conversation — no cross-session contamination.

MANDATORY — ALWAYS call this immediately after session_start. Also call before ANY task that could benefit from context stored earlier in this conversation.

WHEN TO USE:

  • IMMEDIATELY after session_start — to check if there is any context from earlier in this session.

  • When you need to recall what was discussed/decided/stored earlier in THIS conversation.

  • Before starting a new task step — retrieve context about what was done so far.

HOW TO USE THE RESULTS:

  • READ every section of the returned context carefully.

  • APPLY the information to your current task — this is why it was stored.

  • If you see stored decisions or notes, BUILD ON THEM.

  • Do NOT ignore retrieved context — it was stored specifically to help you.

SESSION ISOLATION:

  • Each session starts with ZERO entries — completely fresh.

  • Only returns data stored via memory_store during THIS session.

  • No data from past sessions, global knowledge graph, or vector store is included.

SECTIONS IN OUTPUT:

  • [Current Session]: What has been stored so far in this conversation.

  • [Current Session Notes]: Compressed notes from this session (if working memory was compressed).

TIP: Use a higher token_budget (5000-8000) for comprehensive context. Use lower (1000-2000) for focused lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesWhat to search for. Be descriptive — include project names, tech stack, topic areas. Example: 'user website fate.rf.gd design preferences audio visualizer' rather than just 'website'.
token_budgetNoMax tokens to return. Default 3000. Use 5000-8000 for broad conversation-start context. Use 1000-2000 for focused lookups.
filtersNo
Behavior5/5

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

Since no annotations are provided, the description fully discloses session isolation, cross-session contamination absence, and output sections. No contradictory statements.

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

Conciseness4/5

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

Well-structured with headings, front-loaded core purpose. Some repetition of session isolation, but overall efficient for the amount of guidance provided.

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 nested objects and no output schema, the description adequately covers what to expect (sections), usage scenarios, and tips. Could be more precise on return format, but sufficient for an agent.

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?

Adds usage tips for token_budget (e.g., 5000-8000 for broad context) and explains the query parameter with examples. Schema already covers 67% of parameters, so description adds meaningful but not essential extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves memories from the current session, with emphasis on session isolation. This distinguishes it from siblings like memory_compress, memory_forget, etc., which are for different operations.

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

Usage Guidelines4/5

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

Provides explicit when to use: immediately after session_start and before tasks that benefit from context. Lacks explicit when-not-to-use or direct alternatives, but the context is clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Master0fFate/LatentContext-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server