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IDA Pro MCP

IDA Pro MCP

by Moer2831
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

imports_query

Query imported functions by name or module using filters, count, and offset to inspect imports in IDA Pro databases.

Instructions

Query imports with richer filtering than imports(offset,count).

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": {
      "queries": "<queries>",
      "instance_id": "<instance_id>"
    },
    "name": "imports_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
queriesYesImport query with import/module filters and pagination
instance_idYes必须提供的 instance_id（或 client_id），用于将请求精确路由到特定的 IDA 实例。请先调用 instance_list 查看并选择合适的客户端 ID。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

B3.4/5.0
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, yet it discloses nothing behavioral: no read-only confirmation, no return shape, no pagination/limit semantics, no instance-routing caveats. 'Query' implies a read, but that is inference, not disclosure.

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?

A single tight sentence with the differentiating claim front-loaded and zero filler. It is arguably under-specified rather than bloated, but on the conciseness axis itself it is efficient.

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 read query tool with full schema coverage and no output schema, the parameter story is adequate. However, with no annotations and no explanation of filter syntax or result content, an agent gets only minimal context about what 'richer filtering' yields.

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% (filter, module, count, offset, instance_id all documented in-schema), so the baseline is 3. The description only hints that filter/module exist via 'richer filtering' and adds no syntax or semantics beyond the schema.

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 gives a clear verb+resource ('Query imports') and explicitly positions itself against the sibling tool 'imports(offset,count)' by claiming richer filtering. It falls short of 5 because 'richer filtering' is left vague rather than naming the filter/module dimensions the agent would actually use.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It names the alternative tool ('imports') and the condition that selects this one (need for richer filtering), which is real routing guidance. It lacks any when-not-to-use or detail on what the additional filtering consists of, so it stops short of 5.

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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