ContextForge MCP

memory_query

Read-onlyIdempotent

Search persistent project memory to retrieve prior decisions, architecture notes, and debugging context before answering project questions or making design recommendations.

Instructions

Search persistent memory BEFORE answering any project-specific question. You MUST call this tool: (a) at the start of any conversation that touches the user's codebase, work, or decisions, BEFORE generating any response; (b) whenever the user references prior context ('did we', 'we decided', 'remember', 'what did I save', 'last time'); (c) before making architectural or design recommendations — the user's prior decisions live here. Returns semantically relevant stored content. Skipping this when relevant context exists makes you appear to have amnesia and is the #1 reason users abandon persistent memory — always check first, even if you think you remember.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "memory_query"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Maximum number of results (1-50, default: 10)
`query`	Yes	The search query
`filters`	No	Optional filters
`space_id`	No	Space UUID (uses default if not specified)
`min_score`	No	Minimum similarity score (0-1, default: 0.3)
`project_id`	No	Filter to spaces within this project (auto-set from linked project if not specified)
`include_relationships`	No	Include related items (default: false)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.13.3Nov 11, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. Description adds that it returns semantically relevant content and must be called even if the AI thinks it remembers, which goes beyond the annotations.

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

Conciseness3/5

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

The description is verbose with imperative instructions and repeated emphasis on the consequences of skipping. While informative, it could be more concise and front-loaded.

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?

The description thoroughly covers the tool's role and usage context despite the lack of an output schema. It compensates for the missing return value documentation by stressing the importance of the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description does not add extra meaning beyond the schema's parameter descriptions, focusing instead on usage context.

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 explicitly states 'Search persistent memory' and instructs when to use it before answering project-specific questions, clearly distinguishing it from siblings like memory_get_item or memory_list_items.

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

Usage Guidelines5/5

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

Provides explicit conditions: at conversation start, when prior context is referenced, before architectural decisions. Includes warnings about consequences of skipping, fulfilling the 'when-not' and 'alternatives' implicitly by omission.

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

Deploy Server