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fuzzmind-frida-mcp

fuzzmind-frida-mcp

by fuzzmind
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Python
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frida_memory_alloc

Allocate memory in a target process by specifying process name or PID and size (capped at 10MB). Returns the address of the allocated region.

Instructions

Allocate memory inside a target process via Memory.alloc.

target: process name or pid (string). size: bytes to allocate (capped at 10MB). Returns the address of the allocated region.

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": {
      "target": "<target>",
      "size": "<size>"
    },
    "name": "frida_memory_alloc"
  }
}

Input Schema

NameRequiredDescriptionDefault
targetYes
sizeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description must cover behavioral traits. It mentions allocation via Memory.alloc and returns the address, but does not disclose side effects (e.g., permission needs, whether memory is writable/executable, or if it must be freed). This leaves significant gaps for a memory operation.

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

Conciseness5/5

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

The description is extremely concise with three clear sentences. It uses backtick formatting for parameters and efficiently communicates the core action, constraints, and return value without any filler.

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

Completeness3/5

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

Given the large sibling list and no output schema, the description is adequate for a simple allocation tool but lacks integration context, such as how the allocated memory can be used with other tools (e.g., frida_memory_write) or that it applies to user-space. Complete for the tool itself, but not fully contextual within the ecosystem.

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?

Schema coverage is 0%, so the description compensates well by explaining 'target' as process name or pid and 'size' as bytes capped at 10MB. It adds meaning beyond the schema, though the exact format for target (e.g., string vs integer for pid) is implied but not explicit.

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 allocates memory inside a target process via Memory.alloc, with a specific verb and resource. It implicitly differentiates from kernel allocation by mentioning 'target process', distinguishing it from siblings like frida_kernel_alloc.

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?

The description provides no guidance on when to use this tool versus alternatives (e.g., frida_memory_alloc_string). It only mentions a size cap (10MB) as a constraint, but no explicit when/when-not or alternative suggestions.

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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