Frida Agent MCP

by 1193776794

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execute

Inject Frida JavaScript scripts into Android applications to analyze runtime behavior, retrieve execution data, and perform dynamic reverse engineering tasks.

Instructions

Inject a Frida JavaScript script into the frontmost application. The script is automatically wrapped with try-catch for safety. Returns immediately after injection - use get_messages() to retrieve results after the user has triggered the target functionality.

Args: script: Frida JavaScript code to inject. Use send() to return data. script_file: Path to a .js file to inject. Use this for large scripts instead of script parameter.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`script`	No
`script_file`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 11, 2026

TDQS

A4.5/5.0

Behavior4/5

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

The description reveals key behaviors: automatic try-catch wrapping, immediate return, and result retrieval via get_messages(). With no annotations, this adds necessary transparency, though it omits potential side effects like app crashes.

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, with a clear structure: purpose, safety note, behavior, parameter details. Every sentence adds value.

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?

The description covers parameters and post-injection workflow. It lacks prerequisites like Frida installation or running app, but the output schema likely handles return info. Minor gap.

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?

Both parameters are described with purpose and usage tips: script for code with send(), script_file for large .js files. This compensates for the 0% schema description coverage.

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 injects a Frida JavaScript script into the frontmost application, differentiating it from siblings like connect or detach that perform other actions.

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?

The description instructs to use get_messages() to retrieve results after injection, providing workflow guidance. It could explicitly state when not to use this tool, but the context is sufficient.

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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