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Hex-Rays IDA MCP

Hex-Rays IDA MCP

by zy723
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Batch multi-function analysis

analyze_batch
Read-only

Run comprehensive analysis on one or more target functions and return selected details such as decompilation, disassembly, cross-references, callers, callees, strings, and constants.

Instructions

Run comprehensive analysis over one or more target functions.

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>"
    },
    "name": "analyze_batch"
  }
}

Input Schema

NameRequiredDescriptionDefault
queriesYesComprehensive per-function analysis with selectable sections
instance_idNoOptional database instance id. If omitted, use the current target.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv20261008.0.1

TDQS

C2.9/5.0
Behavior2/5

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

Annotations declare readOnlyHint=true, so the safety profile is covered, but the description adds no behavioral context beyond that: it doesn't warn that analysis is potentially expensive/heavy, note that output volume scales with the number of queries and enabled sections, or mention any timeout or truncation behavior. For a batch tool with 16 per-function toggles this is a real gap.

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 front-loaded sentence with no filler; the purpose arrives immediately. It is efficient but borders on under-specification for a tool with this much configurable surface.

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?

An output schema exists so return values need not be explained, but the description still omits routing versus analyze_function, guidance on section selection, and any note on cost/limits. For a complex batch tool with rich per-query options, one sentence is not sufficient context.

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 every field (addr, include_*, max_*) carries its own description, so the baseline of 3 applies. The description adds nothing about how to shape the queries array or what instance_id does beyond the schema's own note.

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?

States a specific verb (analyze) and resource (target functions) and conveys batch scope via 'one or more', which distinguishes it from a single-function variant. However, it never names the obvious sibling analyze_function or explain what 'comprehensive' entails, so the agent cannot confirm the distinction from the text alone.

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 when-to-use guidance at all: nothing about choosing this over analyze_function, when batching is preferable to repeated single calls, or how instance_id interacts with the current target. The agent must infer usage entirely from the name and schema.

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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