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IDA-MCP

IDA-MCP

by Captain-AI-Hub
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Python
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List Strings

list_strings

Retrieves extracted strings from an open IDA Pro database with pagination and optional pattern or regex filtering, enabling focused review of binary contents.

Instructions

List extracted strings with pagination.

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_strings"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNoNumber of items (1..1000)
regexNoTreat pattern as a regular expression
offsetNoPagination offset (>=0)
patternNoOptional content filter
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?

With no annotations, the description carries the full burden, yet it only notes pagination. It does not describe return shape, ordering, whether results are a snapshot, or the multi-database instance_id requirement (which lives only in the schema). That is thin for a 6-param read tool with no annotations.

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 wasted words. It is efficient but errs toward under-specification, leaving useful space unused rather than adding value.

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 permissive, no-output-schema, no-annotation list tool, the description is barely adequate: it omits how 'extracted strings' are produced and how it relates to get_string. The schema fills the parameter gap, but the behavioral framing remains incomplete.

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 count/offset/regex/pattern/timeout/instance_id are already documented. The description only echoes pagination and adds no syntax or format meaning beyond the schema, making 3 the correct baseline.

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 (List) and resource (extracted strings), so an agent can tell it enumerates strings. However, it does not differentiate from siblings like get_string, search_text, or find_regex, which all touch strings, so the reader must infer the boundary.

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 only contextual hint is 'with pagination'; there is no statement of when to use this over get_string (single-string retrieval), search_text, or find_regex. No prerequisites or exclusions are offered.

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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