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IDA Script MCP

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IDA Script MCP

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English Version

Execute IDAPython scripts in IDA Pro through any MCP-compatible AI assistant.

Why IDA Script MCP?

IDA Script MCP

Latency

< 1ms per request (local HTTP, no IPC overhead)

Footprint

Zero external dependencies inside IDA — stdlib-only plugin

Startup

Plugin ready instantly, no background process in IDA

Concurrency

Run N IDA instances, each on its own port, zero conflict

API Coverage

Full access to 40+ IDA modules including Hex-Rays decompiler

The IDA-side plugin uses only Python stdlib (http.server, socket, json) — no pip packages needed inside IDA Pro. The MCP server (separate process) uses FastMCP for the protocol layer and communicates with IDA via plain HTTP on localhost. This means:

  • No slow startup inside IDA

  • No dependency conflicts with IDA's bundled Python

  • No memory overhead from heavy frameworks loaded into IDA

  • Each IDA instance is completely independent — one crash doesn't affect others

Features

  • AI-Powered Analysis — Let any MCP-compatible AI assistant analyze binaries directly in IDA Pro

  • Multi-Instance Support — Analyze multiple binaries simultaneously across different IDA instances with automatic port assignment

  • Async Task Execution — Long-running scripts won't disconnect the client; poll for results with configurable timeout

  • One-Command Setup — Install IDA plugin + configure your AI client in a single step

  • Full IDA API Access — Complete access to all IDA modules (idaapi, idc, idautils, ida_hexrays, etc.)

  • Jupyter-style Evaluation — Last expression is automatically returned as the result value

  • Output Capture — Capture stdout/stderr and return values from executed code

  • Universal Client Support — Works with any MCP-compatible AI client (see Supported Clients)

Requirements

  • IDA Pro 8.3+ (IDA Free does not support plugins)

  • Python 3.11+

  • Windows / macOS / Linux

Installation

Option 1: pip (Recommended)

pip install ida-script-mcp
ida-script-mcp-install install claude

Option 2: uv

uv pip install ida-script-mcp
ida-script-mcp-install install claude

Option 3: pipx (isolated environment)

pipx install ida-script-mcp
ida-script-mcp-install install claude

Option 4: From Source

git clone https://github.com/SuZiXunYue/ida-script-mcp.git
cd ida-script-mcp
pip install -e .
ida-script-mcp-install install

Advanced Options

# Install plugin only (no client configuration)
ida-script-mcp-install install

# Configure multiple MCP clients at once
ida-script-mcp-install install claude,cursor,cline

# Use project-level configuration (per-repo settings)
ida-script-mcp-install install --project claude

# List all available MCP clients
ida-script-mcp-install --list-clients

# Print raw MCP config JSON (for manual configuration)
ida-script-mcp-install --config

# Uninstall everything
ida-script-mcp-install uninstall claude

Usage

1. Start IDA Plugin

  1. Open IDA Pro and load a binary file

  2. Go to Edit → Plugins → IDA-Script-MCP (or press Ctrl+Alt+S)

  3. Plugin will start and show:

    [IDA-Script-MCP] Server started at http://127.0.0.1:13338
[IDA-Script-MCP] Instance ID: 12345_crackme.exe
[IDA-Script-MCP] Database: crackme.exe

2. Use with AI Assistant

The MCP server provides these tools to your AI assistant:

Tool

Description

list_ida_instances

List all running IDA instances with ports and database info

execute_idapython

Execute Python code in IDA Pro (supports instance_id, port, and timeout)

check_ida_connection

Check connection status and health of all IDA instances

get_ida_database_info

Get database name, path, and platform info

check_task_status

Check the status of a long-running script execution task

Long-Running Scripts

By default, execute_idapython waits up to 600 seconds for a script to complete, polling the IDA plugin for progress. If the script takes longer, a task_id is returned:

{
  "task_id": "a1b2c3d4",
  "status": "running",
  "message": "Script execution timed out after 600s. Use check_task_status with task_id 'a1b2c3d4' to check result later."
}

You can then use check_task_status to query the result once the script finishes:

check_task_status(task_id="a1b2c3d4")

You can also customize the timeout:

execute_idapython(code="long_analysis()", timeout=1800)

3. Example Commands for AI

Ask your AI assistant to:

  • "List all functions in this binary"

  • "Decompile the main function"

  • "Find all xrefs to address 0x401000"

  • "Rename function at 0x401000 to my_function"

  • "Show all strings in the binary"

Supported MCP Clients

This plugin supports all MCP-compatible clients. The installer provides automatic configuration for the following popular clients:

Client

Install Command

Config File

Claude Desktop

ida-script-mcp-install install claude

claude_desktop_config.json

Claude Code

ida-script-mcp-install install claude-code

.claude.json

Cursor

ida-script-mcp-install install cursor

.cursor/mcp.json

VS Code

ida-script-mcp-install install vscode

settings.json

Windsurf

ida-script-mcp-install install windsurf

mcp_config.json

Additional Popular MCP Clients (Manual Configuration)

The following clients are not auto-configured by the installer yet, but work perfectly with IDA Script MCP. Add the config snippet below to the client's MCP settings file:

Client

Config Location

Cline (VS Code extension)

VS Code settings.json → cline.mcpServers

Roo Code (VS Code extension)

.roo/mcp.json

Trae

Trae MCP settings

Augment

Augment MCP settings

Continue

~/.continue/config.json

Copilot (MCP mode)

VS Code settings.json → mcp.servers

Amazon Q Developer

Q Developer MCP settings

Aider

.aider.conf.yml

Any MCP-compatible client

Client's MCP config file

Manual config snippet (add to your client's MCP servers section):

{
  "mcpServers": {
    "ida-script-mcp": {
      "command": "python",
      "args": ["-m", "ida_script_mcp.server"]
    }
  }
}

If you're using a virtual environment, replace "python" with the full path:

# Find your Python path
python -c "import sys; print(sys.executable)"

Configure Multiple Clients at Once

ida-script-mcp-install install claude,cursor,vscode,windsurf

Troubleshooting

Plugin not found in IDA

  • Ensure plugin file is in IDA's plugins directory

  • Check IDA output window for errors

  • Re-run ida-script-mcp-install install

Connection refused

  • Verify IDA Pro is running with a database loaded

  • Confirm plugin is started (Edit → Plugins → IDA-Script-MCP)

  • Check that the port matches in ~/.ida_script_mcp_instances.json

Multiple instances route to wrong IDA

  • This was a Windows-specific bug fixed in v1.0.1 — ensure you're on the latest version

  • Each IDA instance should get a unique port (13338, 13339, 13340, ...)

Script times out / client disconnects

  • Long-running scripts now use async task execution — the server polls for results instead of blocking

  • If you see a task_id in the response, use check_task_status to query the result later

  • Adjust the timeout parameter (default: 600s) if your script needs more time:

    execute_idapython(code="slow_analysis()", timeout=1800)

Command not found

pip show ida-script-mcp
which ida-script-mcp-install

Security Note

This plugin allows arbitrary Python code execution in IDA Pro:

  • Use only with trusted AI assistants

  • Plugin binds to 127.0.0.1 by default (localhost only)

  • Never expose the HTTP port to public networks

License

MIT License

Changelog

[1.2.0] - 2026-05-08

Added:

  • Async task execution system: Long-running scripts no longer cause client disconnection. Scripts are submitted asynchronously to IDA, and the MCP server polls for completion with exponential backoff (0.5s → 5s cap). If the configurable timeout (default: 600s) is exceeded, a task_id is returned for later status queries.

  • check_task_status tool: New MCP tool to query the status and result of a long-running script execution task by its task_id.

  • timeout parameter for execute_idapython: Configurable maximum wait time (default: 600 seconds) before returning a task_id for deferred polling.

  • Task management endpoints in IDA plugin: GET /task/{id} to query task status/result, GET /tasks to list all tasks.

  • async mode for POST /execute: IDA plugin now accepts {"async": true} to submit scripts for background execution and immediately return a task_id.

  • ThreadingMixIn HTTP server: The IDA plugin HTTP server now handles each request in a separate thread, preventing a single long-running script from blocking other requests (e.g., health checks, task status queries).

Fixed:

  • Client disconnection on long-running scripts: Previously, scripts running longer than 60 seconds would cause the MCP server's HTTP connection to IDA to time out, while the script continued running in IDA with no way to retrieve the result. The new async task system eliminates this issue.

  • HTTP server blocking: The IDA plugin's single-threaded HTTP server could be blocked by a running script, making all other endpoints (health, metadata) unreachable. Switched to ThreadingMixIn for concurrent request handling.

[1.1.0] - 2026-04-16

Fixed:

  • Windows multi-instance port collision: On Windows, all IDA instances would bind to the same port (13338) because SO_REUSEADDR allows multiple processes to bind the same port without error. Fixed by disabling allow_reuse_address on Windows and adding pre-bind port detection.

[1.0.0] - 2024-01-15

Added:

  • Initial release with list_ida_instances, execute_idapython, check_ida_connection, get_ida_database_info tools.

  • Multi-instance support, auto-discovery, full IDA API access, Jupyter-style evaluation, cross-platform support.

Related MCP server: IDAssistMCP

中文版本

通过任何支持 MCP 协议的 AI 助手，在 IDA Pro 中执行 IDAPython 脚本。

为什么选择 IDA Script MCP？

IDA Script MCP

延迟

每次请求 < 1ms（本地 HTTP，无 IPC 开销）

资源占用

IDA 内零外部依赖 — 插件仅使用标准库

启动速度

插件即时就绪，IDA 内无后台进程

并发能力

运行 N 个 IDA 实例，各自独立端口，互不冲突

API 覆盖

完整访问 40+ IDA 模块，包括 Hex-Rays 反编译器

IDA 端插件仅使用 Python 标准库（http.server、socket、json）——无需在 IDA Pro 中安装任何 pip 包。MCP 服务器（独立进程）使用 FastMCP 作为协议层，通过本地 HTTP 与 IDA 通信。这意味着：

  • IDA 内无缓慢启动

  • 不与 IDA 内置 Python 产生依赖冲突

  • 不因加载重框架而占用 IDA 内存

  • 每个 IDA 实例完全独立 — 一个崩溃不影响其他

特性

  • AI 驱动分析 — 让任何支持 MCP 的 AI 助手直接在 IDA Pro 中分析二进制文件

  • 多实例支持 — 同时分析多个二进制文件，自动分配端口，实例间互不干扰

  • 异步任务执行 — 长时间运行的脚本不会导致客户端断开连接；可配置超时，轮询获取结果

  • 一键安装 — 一条命令完成 IDA 插件安装和 AI 客户端配置

  • 完整 IDA API 访问 — 完全访问所有 IDA 模块（idaapi、idc、idautils、ida_hexrays 等）

  • Jupyter 风格求值 — 自动返回最后一个表达式的值

  • 输出捕获 — 捕获执行代码的标准输出/错误和返回值

  • 通用客户端支持 — 兼容所有支持 MCP 协议的客户端（见支持客户端）

系统要求

  • IDA Pro 8.3+（IDA Free 不支持插件）

  • Python 3.11+

  • Windows / macOS / Linux

安装

方式一：pip（推荐）

pip install ida-script-mcp
ida-script-mcp-install install claude

方式二：uv

uv pip install ida-script-mcp
ida-script-mcp-install install claude

方式三：pipx（隔离环境）

pipx install ida-script-mcp
ida-script-mcp-install install claude

方式四：从源码安装

git clone https://github.com/SuZiXunYue/ida-script-mcp.git
cd ida-script-mcp
pip install -e .
ida-script-mcp-install install

高级选项

# 仅安装插件（不配置客户端）
ida-script-mcp-install install

# 同时配置多个 MCP 客户端
ida-script-mcp-install install claude,cursor,cline

# 使用项目级配置（每个仓库独立设置）
ida-script-mcp-install install --project claude

# 列出所有可用的 MCP 客户端
ida-script-mcp-install --list-clients

# 打印 MCP 配置 JSON（用于手动配置）
ida-script-mcp-install --config

# 卸载
ida-script-mcp-install uninstall claude

使用方法

1. 启动 IDA 插件

  1. 打开 IDA Pro 并加载二进制文件

  2. 进入 Edit → Plugins → IDA-Script-MCP（或按 Ctrl+Alt+S）

  3. 插件启动后会显示：

    [IDA-Script-MCP] Server started at http://127.0.0.1:13338
[IDA-Script-MCP] Instance ID: 12345_crackme.exe
[IDA-Script-MCP] Database: crackme.exe

2. 使用 AI 助手

MCP 服务器为 AI 助手提供以下工具：

工具

说明

list_ida_instances

列出所有运行中的 IDA 实例及其端口和数据库信息

execute_idapython

在 IDA Pro 中执行 Python 代码（支持 instance_id、port 和 timeout）

check_ida_connection

检查所有 IDA 实例的连接状态和健康信息

get_ida_database_info

获取数据库名称、路径和平台信息

check_task_status

查询长时间运行的脚本执行任务的状态

长时间运行的脚本

默认情况下，execute_idapython 最多等待 600 秒让脚本完成，期间会轮询 IDA 插件获取进度。如果脚本执行时间超过该限制，会返回一个 task_id：

{
  "task_id": "a1b2c3d4",
  "status": "running",
  "message": "Script execution timed out after 600s. Use check_task_status with task_id 'a1b2c3d4' to check result later."
}

脚本完成后，可使用 check_task_status 查询结果：

check_task_status(task_id="a1b2c3d4")

也可以自定义超时时间：

execute_idapython(code="long_analysis()", timeout=1800)

3. 示例命令

让 AI 助手执行：

  • "列出此二进制文件中的所有函数"

  • "反编译 main 函数"

  • "查找地址 0x401000 的所有交叉引用"

  • "将地址 0x401000 的函数重命名为 my_function"

  • "显示二进制文件中的所有字符串"

支持的 MCP 客户端

本插件支持所有兼容 MCP 协议的客户端。 安装器为以下常用客户端提供自动配置：

客户端

安装命令

配置文件

Claude Desktop

ida-script-mcp-install install claude

claude_desktop_config.json

Claude Code

ida-script-mcp-install install claude-code

.claude.json

Cursor

ida-script-mcp-install install cursor

.cursor/mcp.json

VS Code

ida-script-mcp-install install vscode

settings.json

Windsurf

ida-script-mcp-install install windsurf

mcp_config.json

更多常用 MCP 客户端（手动配置）

以下客户端暂未纳入安装器自动配置，但完全兼容 IDA Script MCP。将下方配置片段添加到客户端的 MCP 设置中即可：

客户端

配置位置

Cline（VS Code 扩展）

VS Code settings.json → cline.mcpServers

Roo Code（VS Code 扩展）

.roo/mcp.json

Trae

Trae MCP 设置

Augment

Augment MCP 设置

Continue

~/.continue/config.json

Copilot（MCP 模式）

VS Code settings.json → mcp.servers

Amazon Q Developer

Q Developer MCP 设置

Aider

.aider.conf.yml

任何支持 MCP 的客户端

客户端 MCP 配置文件

手动配置片段（添加到客户端的 MCP 服务器配置中）：

{
  "mcpServers": {
    "ida-script-mcp": {
      "command": "python",
      "args": ["-m", "ida_script_mcp.server"]
    }
  }
}

如果使用虚拟环境，将 "python" 替换为完整路径：

# 查看 Python 路径
python -c "import sys; print(sys.executable)"

同时配置多个客户端

ida-script-mcp-install install claude,cursor,vscode,windsurf

故障排除

在 IDA 中找不到插件

  • 确认插件文件在 IDA 的 plugins 目录中

  • 检查 IDA 输出窗口的错误信息

  • 重新运行 ida-script-mcp-install install

连接被拒绝

  • 确保 IDA Pro 正在运行且已加载数据库

  • 确认插件已启动（Edit → Plugins → IDA-Script-MCP）

  • 检查 ~/.ida_script_mcp_instances.json 中的端口是否正确

多实例路由到错误的 IDA

  • 这是 Windows 上的已知问题，已在 v1.0.1 中修复 — 请确保使用最新版本

  • 每个 IDA 实例应获得唯一端口（13338、13339、13340……）

脚本超时 / 客户端断开

  • 长时间运行的脚本现在使用异步任务执行 — 服务器会轮询获取结果而非阻塞等待

  • 如果响应中包含 task_id，可使用 check_task_status 稍后查询结果

  • 可通过 timeout 参数调整等待时间（默认 600 秒）：

    execute_idapython(code="slow_analysis()", timeout=1800)

找不到命令

pip show ida-script-mcp
which ida-script-mcp-install

安全提示

此插件允许在 IDA Pro 中执行任意 Python 代码：

  • 仅与可信的 AI 助手一起使用

  • 插件默认绑定到 127.0.0.1（仅本地访问）

  • 切勿将 HTTP 端口暴露到公网

许可证

MIT License

更新日志

[1.2.0] - 2026-05-08

新增：

  • 异步任务执行系统：长时间运行的脚本不再导致客户端断开连接。脚本异步提交到 IDA，MCP 服务器以指数退避策略（0.5s → 5s 上限）轮询完成状态。如果超过可配置的超时时间（默认 600 秒），会返回 task_id 供后续查询。

  • check_task_status 工具：新增 MCP 工具，通过 task_id 查询长时间运行的脚本执行任务的状态和结果。

  • execute_idapython 的 timeout 参数：可配置最大等待时间（默认 600 秒），超时后返回 task_id 以便延迟轮询。

  • IDA 插件任务管理端点：GET /task/{id} 查询任务状态/结果，GET /tasks 列出所有任务。

  • POST /execute 的 async 模式：IDA 插件现在接受 {"async": true} 以提交脚本进行后台执行，并立即返回 task_id。

  • ThreadingMixIn HTTP 服务器：IDA 插件 HTTP 服务器现在在独立线程中处理每个请求，防止单个长时间运行的脚本阻塞其他请求（如健康检查、任务状态查询）。

修复：

  • 长时间运行脚本导致客户端断开：此前，运行超过 60 秒的脚本会导致 MCP 服务器到 IDA 的 HTTP 连接超时，而脚本在 IDA 中继续运行但无法获取结果。新的异步任务系统解决了此问题。

  • HTTP 服务器阻塞：IDA 插件的单线程 HTTP 服务器可被运行中的脚本阻塞，导致所有其他端点（health、metadata）不可达。改用 ThreadingMixIn 实现并发请求处理。

[1.1.0] - 2026-04-16

修复：

  • Windows 多实例端口冲突：在 Windows 上，所有 IDA 实例会绑定到同一端口 (13338)，因为 SO_REUSEADDR 允许多个进程无错误地绑定同一端口。通过在 Windows 上禁用 allow_reuse_address 并添加绑定前端口检测来修复。

[1.0.0] - 2024-01-15

新增：

  • 初始发布，包含 list_ida_instances、execute_idapython、check_ida_connection、get_ida_database_info 工具。

  • 多实例支持、自动发现、完整 IDA API 访问、Jupyter 风格求值、跨平台支持。

Available Tools

5 tools
check_ida_connectionA
Read-onlyIdempotent

Check if IDA Pro instances are running and accessible.

Returns: str: JSON-formatted string with connection status and all instances.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. Description adds that it returns a JSON-formatted string with connection status and instances, providing return format context beyond annotations.

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?

Two effective sentences: one for purpose, one for return. Front-loaded, no filler, every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool is simple (0 params, output schema exists). Description adequately covers purpose and return format for a connection check, though could mention lightweight nature given annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters with 100% schema coverage, so baseline is 4. Description does not need to add param info and appropriately omits it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description states specific verb+resource ('Check if IDA Pro instances are running and accessible'), clearly distinguishing it from siblings like list_ida_instances which may only list without checking accessibility.

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

Usage Guidelines3/5

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

No explicit guidance on when to use this vs alternatives (e.g., list_ida_instances). The purpose implies it's for verifying connectivity, but lacks when-not-to-use or condition-based selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

check_task_statusA
Read-onlyIdempotent

Check the status of a long-running script execution task.

Use this tool when execute_idapython returns a task_id with status 'running' or 'pending', indicating the script is still executing in IDA Pro and the timeout was exceeded.

Args: task_id: The task ID returned by execute_idapython instance_id: Target IDA instance ID (optional, uses default if not specified) port: Target IDA instance port (optional, uses default if not specified)

Returns: str: JSON-formatted task status with result if completed.

ParametersJSON Schema
NameRequiredDescriptionDefault
task_idYes
instance_idNo
portNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds behavioral context by explaining the tool's role in polling a long-running task and specifying the return format (JSON status with result). No contradictions.

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?

Description is concise (4 sentences) with purpose front-loaded. Every sentence adds value, no fluff. Structure includes clear Args section and Return description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and the presence of an output schema, the description adequately covers usage, parameters, and return. It references the related execute_idapython tool, providing necessary context for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description provides full parameter descriptions: task_id is 'The task ID returned by execute_idapython', instance_id and port are optional with defaults explained. This adds significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check the status of a long-running script execution task.' It specifies the verb (check) and resource (task status), and distinguishes from siblings by referencing the task_id from execute_idapython.

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

Usage Guidelines5/5

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

Explicitly states when to use: 'when execute_idapython returns a task_id with status running or pending.' This provides clear context and implicitly tells when not to use (e.g., if status is completed).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

execute_idapythonA
Destructive

Execute Python code or script file in IDA Pro context.

This tool sends Python code to the IDA Pro plugin for execution. The code runs in IDA's main thread with full access to all IDA API modules.

For long-running scripts, the tool polls for completion up to the timeout. If the timeout is exceeded, a task_id is returned so you can check status later using the check_task_status tool.

Args: params (ExecuteScriptInput): Validated input parameters containing: - code (Optional[str]): Python code string to execute - script_path (Optional[str]): Path to Python script file - capture_output (bool): Whether to capture stdout/stderr - instance_id (Optional[str]): Target IDA instance ID (e.g., "crackme.exe" or full ID) - port (Optional[int]): Target IDA instance port (e.g., 13338) - timeout (int): Maximum wait time in seconds (default: 600)

Returns: str: JSON-formatted string containing: - result: The return value of the last expression - stdout: Captured standard output - stderr: Captured standard output (including errors) - instance: The IDA instance that executed the code - task_id: Present if script is still running or timed out

Examples: # Execute on default instance execute_idapython(code="print(idaapi.get_root_filename())")

# Execute on specific instance by database name
execute_idapython(code="len(list(idautils.Functions()))", instance_id="crackme.exe")

# Execute on specific instance by port
execute_idapython(code="idc.get_func_name(0x401000)", port=13339)
ParametersJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations (destructiveHint: true), the description details execution in IDA's main thread, polling with timeout, and returning a task_id for async status checks. No contradictions.

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 well-organized with clear sections (summary, execution behavior, Args, Returns, Examples). It is somewhat verbose but all content is necessary for a complex tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all aspects: execution context, timeout handling, return format (result, stdout, stderr, instance, task_id), and examples. No gaps given the tool's complexity and available annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite schema having partial descriptions, the description's Args block adds valuable context: default values, the mutual exclusivity of code and script_path, and timeout behavior. Examples illustrate parameter use.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Execute Python code or script file in IDA Pro context.' It distinguishes from sibling tools like check_ida_connection and check_task_status by focusing on code execution with explicit examples.

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

Usage Guidelines5/5

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

The description explains when to use (to execute code in IDA) and when to use the sibling check_task_status tool for checking long-running scripts. Provides examples for default and specific instances, guiding the agent on proper usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_ida_database_infoA
Read-onlyIdempotent

Get information about an IDA database.

Args: instance_id: Target IDA instance ID (optional, uses default if not specified).

Returns: str: JSON-formatted string with database information.

ParametersJSON Schema
NameRequiredDescriptionDefault
instance_idNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, destructiveHint, and idempotentHint, covering safety and idempotency. The description adds the return format (JSON string) but does not disclose other behavioral traits beyond what annotations provide.

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 extremely concise, with three short sentences covering purpose, parameters, and returns. No redundant information; every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only information tool with strong annotations, the description is complete: it specifies the action, parameter semantics, and return format. The sibling context provides differentiation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description adds necessary meaning: it explains that instance_id is 'Target IDA instance ID (optional, uses default if not specified)', clarifying its role and default behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get information about an IDA database', specifying the verb and resource. It distinguishes itself from sibling tools like execute_idapython or list_ida_instances, which have different purposes.

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 description explains when to use the tool (to get database info) and mentions the optional instance_id, but lacks explicit guidance on when not to use it or how it differs from alternatives like check_ida_connection or check_task_status.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_ida_instancesA
Read-onlyIdempotent

List all running IDA instances with MCP plugin enabled.

Returns: str: JSON-formatted list of IDA instances with their ports and database info.

Example response: { "count": 2, "instances": { "12345_crackme.exe": {"port": 13338, "database": "crackme.exe"}, "67890_malware.dll": {"port": 13339, "database": "malware.dll"} } }

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds valuable context by specifying that only running instances with the MCP plugin are listed and provides the return format with an example, including count and instance details.

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 concise: one sentence for purpose, then return format and example. Every sentence adds value, no redundancy. Front-loaded with the main action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, clear purpose, and output schema described in the description), the description is complete. It covers what the tool does, what it returns, and provides a concrete example. No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the input schema is fully covered. Per guidelines, 0 parameters yields a baseline of 4. The description adds no parameter info, but none is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool lists all running IDA instances with the MCP plugin enabled, specifying the verb 'List' and the resource 'running IDA instances'. It implicitly distinguishes from sibling tools like 'execute_idapython' and 'check_ida_connection', which perform different actions.

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 explicit guidance on when to use this tool versus alternatives. While the purpose is clear, there is no mention of when not to use it or which sibling tool might be more appropriate for specific scenarios, such as checking a single connection or executing scripts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 5 tool updatesv1.2.0
    • First observedcheck_ida_connection
    • First observedcheck_task_status
    • First observedexecute_idapython
    • First observedget_ida_database_info
    • First observedlist_ida_instances
Install Server
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TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a distinct purpose: checking connection, listing instances, getting database info, executing scripts, and checking task status. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., check_ida_connection, execute_idapython), making them predictable and easy to understand.

Tool Count5/5

Five tools is an ideal size for this server's purpose—covering connection management, instance listing, database info, script execution, and status checking without being over or underscoped.

Completeness5/5

The tool set covers all essential operations for executing scripts in IDA Pro: checking connectivity, listing instances, retrieving database info, executing code, and monitoring long-running tasks. No obvious gaps.

Maintenance

ActivityInactive
ResponsivenessWithin a week

Resources

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