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Cursor10x MCP

Cursor10x MCP

by aiurda
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

getComprehensiveContext

Retrieve comprehensive context from all memory systems using semantic search to enhance AI assistant capabilities in retaining short-term, long-term, and episodic memory.

Instructions

Retrieves comprehensive context from all memory systems

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "getComprehensiveContext"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNoOptional query for semantic search to find relevant context

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves context but doesn't clarify whether this is a read-only operation, what permissions might be needed, how results are formatted, or any performance implications (e.g., latency, rate limits). This leaves significant gaps for a tool that presumably accesses multiple systems.

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?

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action, though it could be slightly more specific to improve clarity without sacrificing brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete for a tool that retrieves 'comprehensive context.' It doesn't explain what 'comprehensive' means, what systems are involved, the format of returned data, or any limitations, making it inadequate for an agent to understand the full scope and behavior.

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?

The schema description coverage is 100%, with the single parameter 'query' documented as optional and for semantic search. The description adds no additional meaning beyond this, such as examples of queries or how they influence retrieval. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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

Purpose3/5

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

The description states the action ('Retrieves') and target ('comprehensive context from all memory systems'), which is clear but vague. It doesn't specify what 'comprehensive context' entails or how it differs from sibling tools like getRecentEpisodes or getRecentMessages, leaving room for ambiguity about scope and content.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. With siblings like getRecentEpisodes and getRecentMessages that might retrieve specific subsets of context, the description lacks any indication of appropriate use cases, prerequisites, or exclusions, leaving the agent to guess based on the tool name alone.

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

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