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IDA-MCP

IDA-MCP

by Captain-AI-Hub
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Make Data

make_data

Converts an address into typed data items like bytes or words, enabling reverse engineers to define data structures in IDA Pro.

Instructions

Create typed data items at an address.

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": {
      "address": "<address>",
      "data_type": "<data_type>"
    },
    "name": "make_data"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNoNumber of items to create
addressYesAddress to convert into typed data
timeoutNoTimeout in seconds
data_typeYesData type: byte, word, dword, qword, oword, float, double, pointer
instance_idNoREQUIRED whenever more than one database is open (from open_database's result or list_databases()); optional only while exactly one instance is live.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.1
    • changedInput schema / properties / instance_id / description
      Previous value: -"Instance id override"New value: +"REQUIRED whenever more than one database is open (from open_database's result or list_databases()); optional only while exactly one instance is live."
  2. First observedv0.9.7

TDQS

C2.9/5.0
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 behavioral burden. It says only that typed data items are created, without explaining whether it overwrites existing definitions, what permissions are needed, how it affects disassembly, or the role of instance_id in mutation semantics.

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 front-loaded sentence with no filler. It is concise, though arguably too terse for a mutation tool with five parameters and no annotations.

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?

The tool mutates database contents and has no annotations or output schema, so the description should explain side effects and constraints. Instead, it provides only a bare purpose statement, leaving significant behavioral context to inference.

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 schema already documents all five parameters, including data_type values and instance_id requirements. The description adds no parameter-specific meaning beyond restating that typed data is created at an address.

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

Purpose4/5

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

The description states a specific verb and resource: create typed data items at an address. It is clear enough to distinguish from make_code and make_string, which deal with code and strings respectively, though it does not explicitly name those alternatives.

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 when-to-use guidance, prerequisites, or alternatives. An agent must infer that this is the correct tool for defining typed data rather than code, strings, or bytes.

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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