Skip to main content
Glama

load_executable

Load executable binaries (ELF, PE, Mach-O) into the MCPEmulate emulator to analyze and execute code across multiple CPU architectures.

Instructions

Load an executable binary (ELF, PE, or Mach-O) into the emulator.

Auto-detects format. Maps segments with correct permissions, sets PC to entry point, registers symbols.

Args: session_id: The session ID. data: Binary data as hex string or base64. base_address: Optional base address offset. Default 0. encoding: "hex" (default) or "base64".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYes
dataYes
base_addressNo
encodingNohex
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions behavioral aspects like auto-detecting format, mapping segments with permissions, setting PC to entry point, and registering symbols, which are useful. However, it lacks critical details such as error handling, performance implications, side effects on the emulator state, or whether this is a read-only or mutating 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 front-loaded with the core purpose in the first sentence, followed by behavioral details and a well-structured parameter list. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 complexity of loading executables into an emulator, no annotations, and no output schema, the description is moderately complete. It covers the purpose, parameters, and some behavioral traits but lacks details on return values, error cases, and integration with sibling tools, leaving gaps for an AI agent to infer.

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 description coverage is 0%, so the description must compensate. It provides clear semantics for all 4 parameters: 'session_id' (The session ID), 'data' (Binary data as hex string or base64), 'base_address' (Optional base address offset. Default 0), and 'encoding' ("hex" (default) or "base64"). This adds significant value beyond the bare schema, though it could include more detail on data formats or constraints.

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 the specific action ('Load an executable binary') and the target resource ('into the emulator'), with explicit format support (ELF, PE, or Mach-O). It distinguishes from sibling tools like 'load_binary' by specifying executable loading with auto-detection and setup features (maps segments, sets PC, registers symbols).

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 like 'load_binary' or 'map_memory'. The description implies usage for loading executables but does not specify prerequisites, exclusions, or contextual triggers for selection among similar tools.

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/LabGuy94/MCPEmulate'

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