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IDA Pro MCP

IDA Pro MCP

by icryo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_xrefs_to

Retrieve all cross references pointing to a specific address in IDA Pro to analyze code relationships and data flows during reverse engineering.

Instructions

Get all cross references to the given 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>"
    },
    "name": "get_xrefs_to"
  }
}

Input Schema

NameRequiredDescriptionDefault
addressYesAddress to get cross references to

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.6.0

TDQS

B3.1/5.0
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 cross references but doesn't describe what 'cross references' entail (e.g., code/data references, directionality), output format, pagination, or error handling. This leaves significant gaps for a tool that likely queries a complex system like a disassembler or debugger.

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 a single, efficient sentence with no wasted words. It front-loads the core purpose ('Get all cross references') and is appropriately sized for a simple query tool, making it easy for an agent to parse quickly.

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 tool has an output schema (which should define return values) and high schema coverage for its single parameter, the description is minimally adequate. However, without annotations and with many sibling tools in a complex domain (e.g., reverse engineering), it lacks context on behavior, limitations, and differentiation, leaving room for improvement.

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%, with the parameter 'address' clearly documented in the schema. The description adds minimal value by mentioning 'given address' but doesn't elaborate on address format (e.g., hex, virtual address), validation, or examples beyond what the schema provides, meeting the baseline for high schema coverage.

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 clearly states the action ('Get') and target resource ('cross references'), specifying the input ('given address'). It distinguishes from sibling 'get_xrefs_to_field' by focusing on address-level cross-references rather than field-level, though it doesn't explicitly mention this distinction.

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 'get_callees', 'get_callers', or 'get_xrefs_to_field'. The description lacks context about prerequisites, typical use cases, or exclusions, leaving the agent to infer usage from 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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