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IDA-MCP

IDA-MCP

by Captain-AI-Hub
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Python
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List Segments

list_segments

Lists memory segments and their permissions for an open IDA Pro database, helping you inspect binary layout and segment access rights. Use the instance ID when multiple databases are open.

Instructions

List memory segments with permissions.

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": "list_segments"
  }
}

Input Schema

NameRequiredDescriptionDefault
timeoutNoTimeout in seconds
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 present, so the description carries the full behavioral burden. It implies a read-only listing but does not state whether an open database is required, what permissions mean, whether results are paginated, or what the return shape is.

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 wasted words. It is concise, though its brevity contributes to gaps handled in other dimensions rather than being a conciseness flaw.

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?

For a simple two-parameter listing tool with fully documented schema parameters, the description is minimally adequate. However, with no output schema and no annotations, it should do more to explain the returned segment data and the instance_id dependency beyond what the schema states.

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%, and the schema itself fully documents timeout and the instance_id requirement, so the baseline is 3. The description adds no additional parameter meaning beyond what the schema already provides.

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: "List memory segments." It is clearly distinct from add_segment and delete_segment by name, though the added phrase "with permissions" is vague and not explained.

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?

It gives no guidance on when to use this tool versus alternatives, nor any prerequisites. The list verb implies usage, but no explicit context or exclusions are provided.

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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