Android Forensics ADB MCP Server
Allows forensic acquisition from Android devices via ADB, including device backup, extraction of forensic artifacts, execution of whitelisted shell commands, and retrieval of device information and installed packages.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Android Forensics ADB MCP Serverpull all forensic artifacts from the connected device"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Android Forensics ADB MCP Server
A comprehensive Model Context Protocol (MCP) server for Android device forensic data acquisition using Android Debug Bridge (ADB). This tool is designed for forensic investigators with proper consent and authorization.
⚠️ Legal Notice
This tool is intended for authorized forensic investigations only. Users must have:
Legal authorization to access the device
Written consent from the device owner
Compliance with local laws and regulations
Proper chain of custody documentation
Unauthorized access to devices is illegal and unethical.
Related MCP server: Enhanced ADB MCP Server
Features
Core Capabilities
Device Management: Connect and manage Android devices via ADB
Secure Command Execution: Whitelisted shell commands for safety
Full Device Backup: Create complete device backups (.ab format)
Backup Extraction: Convert Android Backup (.ab) to TAR format (Python port of adb-backup-extract)
Data Acquisition: Pull specific files and directories
Forensic Artifact Collection: Automated collection of common forensic artifacts
Metadata & Chain of Custody: Automatic forensic metadata generation
MCP Tools Available
check_adb_status: Verify ADB installation and availability
adb_devices: List all connected Android devices
adb_connect_device: Connect to specific device
adb_shell_command: Execute whitelisted shell commands
get_device_info: Get comprehensive device information
list_installed_packages: List all installed applications
adb_backup_device: Create full device backup
adb_pull_data: Pull files/folders from device
extract_backup_to_tar: Extract .ab backups to TAR format
collect_forensic_artifacts: Automated artifact collection
Prerequisites
Required Software
Python 3.13+: Required for the MCP server
Android Platform Tools: Install ADB
Download: https://developer.android.com/tools/releases/platform-tools
Add to system PATH
UV Package Manager: Already configured in your environment
Android Device Requirements
USB Debugging enabled (Settings → Developer Options → USB Debugging)
Device unlocked during data acquisition
USB cable connection or network ADB connection
Installation
Install Dependencies:
uv syncVerify ADB Installation:
adb versionTest the Server:
uv run mcp dev main.pyUsage
Running the Server
Development Mode (with MCP Inspector)
uv run mcp dev main.pyProduction Mode (Claude Desktop Integration)
uv run mcp install main.py --name "Android Forensics"Claude Desktop Configuration
Add to claude_desktop_config.json:
{
"mcpServers": {
"android-forensics": {
"command": "uv",
"args": [
"--directory",
"u:\\adb-connect",
"run",
"main.py"
],
"env": {
"PYTHONUNBUFFERED": "1"
}
}
}
}Example Workflows
1. Basic Device Connection
1. Check ADB status: check_adb_status()
2. List devices: adb_devices()
3. Connect to device: adb_connect_device(device_id="DEVICE_SERIAL")
4. Get device info: get_device_info(device_id="DEVICE_SERIAL")2. Full Device Backup
1. Create backup:
adb_backup_device(
output_file="evidence_backup.ab",
device_id="DEVICE_SERIAL",
include_apk=True,
include_shared=True,
all_apps=True
)
2. Extract backup:
extract_backup_to_tar(
backup_file="evidence_backup.ab",
output_tar="evidence_backup.tar",
password="optional_password"
)3. Collect Forensic Artifacts
collect_forensic_artifacts(
output_dir="./forensic_evidence",
device_id="DEVICE_SERIAL"
)4. Execute Shell Commands
adb_shell_command(
command="pm list packages",
device_id="DEVICE_SERIAL"
)Security Features
Command Whitelisting
Only the following shell commands are allowed:
File operations:
ls,cat,pwd,find,du,dfSystem info:
getprop,dumpsys,uname,date,uptimePackage management:
pm,amProcess management:
ps,topNetwork:
netstat,ip,ifconfigLogs:
logcatSettings:
settings,contentScreen:
screencap,wm
Validation
Commands are validated before execution
Shell operators (
;,&&,||,|) are checkedTimeout limits prevent hanging processes
Error handling for all operations
Backup Extraction Details
The extract_backup_to_tar tool is a Python implementation of the adb-backup-extract project.
Supported Features
✅ Unencrypted backups
✅ Encrypted backups (with password)
✅ Compressed backups (zlib)
✅ AES-256 decryption
✅ PBKDF2 key derivation
Backup File Format
Android backups (.ab) have the following structure:
ANDROID BACKUP\n
version\n
compressed (0 or 1)\n
encryption (none or AES-256)\n
[encryption metadata if encrypted]
[compressed/encrypted data]Forensic Best Practices
Chain of Custody
All operations generate metadata including:
Timestamp (ISO 8601 format)
Device serial number
Operation performed
Investigator information
File hashes (where applicable)
Evidence Collection
Document Everything: Use
get_device_info()firstCreate Full Backup: Use
adb_backup_device()for complete acquisitionHash Evidence: Calculate SHA-256 hashes of all collected files
Maintain Logs: Keep all command outputs and errors
Write-Protect Evidence: Store backups as read-only immediately
Recommended Workflow
1. Connect device and verify connection
2. Document device information
3. Take screenshots of device state
4. Create full backup
5. Extract backup to TAR
6. Collect specific artifacts
7. Generate forensic report
8. Calculate and document all hashes
9. Store evidence securelyTroubleshooting
ADB Not Found
# Windows: Add to PATH or use full path
$env:PATH += ";C:\path\to\platform-tools"
# Verify
adb versionDevice Not Detected
Enable USB Debugging on device
Accept RSA fingerprint on device
Try different USB cable/port
Check
adb devicesoutput
Backup Fails
Ensure device is unlocked
Confirm backup on device screen
Check available storage
Some apps may block backup
Permission Denied
Many forensic artifacts require root access
Use
adb rootif device is rootedConsider using TWRP recovery for full access
Architecture
Project Structure
adb-connect/
├── main.py # MCP server implementation
├── pyproject.toml # Dependencies and configuration
├── README.md # This file
└── .python-version # Python version specificationKey Components
MCP Server: FastMCP-based server with tool registration
ADB Wrapper: Safe command execution with subprocess
Backup Extractor: Cryptography-based .ab to .tar converter
Forensic Collectors: Automated artifact acquisition
Metadata Generator: Chain of custody documentation
Dependencies
mcp[cli] >= 1.19.0: Model Context Protocol SDK
cryptography >= 43.0.0: Backup decryption (AES-256, PBKDF2)
pydantic >= 2.0.0: Data validation and serialization
Contributing
This is a forensic tool - contributions should prioritize:
Security and safety
Legal compliance
Evidence integrity
Documentation quality
References
License
MIT License - See LICENSE file for details.
Disclaimer
This tool is provided for legitimate forensic investigations only. The authors and contributors are not responsible for any misuse or illegal activities. Always ensure you have proper authorization before accessing any device.
For Forensic Investigation Departments: This tool is designed to support your authorized investigations with full respect for legal requirements and chain of custody procedures.
Available Tools
10 toolsanalyze_network_connectionsA
Analyze active network connections and configuration. Identifies connected networks, open ports, and suspicious connections.
Args: device_id: Optional device serial number output_file: Optional path to save results as JSON
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No | ||
| output_file | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only mentions high-level analysis and outputs. It does not state whether the tool requires special permissions, performs active scanning, or has side effects like writing to the output file.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded, with two sentences of purpose followed by a concise parameter list. Every sentence contributes value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The presence of an output schema covers return values, but the description lacks operational context such as permission requirements, potential network impact, and the meaning of 'suspicious connections.' The tool is moderately complex, so more context would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning with an Args section, explaining device_id as an optional device serial number and output_file as a path to save JSON results. This goes beyond the bare schema titles, though it omits any detailed constraints or interactions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes active network connections and configuration, listing specific outputs like connected networks, open ports, and suspicious connections. This differentiates it from sibling tools focused on logs, processes, or packages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for network analysis but provides no explicit guidance on when to prefer this tool over alternatives, nor any exclusions or prerequisites. It is not misleading but leaves the agent to infer the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
analyze_partition_infoA
Analyze device partitions and mount points. Essential for understanding device storage layout.
Args: device_id: Optional device serial number output_file: Optional path to save results as JSON
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No | ||
| output_file | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It does not state whether the operation is read-only, whether root or special permissions are required, or what side effects (beyond writing an optional output file) might occur. The term 'analyze' implies non-destructive introspection, but this is not explicit, and prerequisites like device connectivity are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences stating purpose and context, followed by a three-line Args list that adds parameter detail. It is front-loaded with the core purpose and contains no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (two optional params, no nested objects) and the presence of an output schema, the description covers the essential aspects: purpose, usage context, and parameter meanings. Minor gaps include not mentioning device prerequisites (e.g., whether a device must be connected) or root requirements, but these are not critical given the output schema and simple nature.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. The Args section provides meaningful semantics for both parameters: device_id is described as 'device serial number' and output_file as 'path to save results as JSON,' adding value beyond the bare schema properties. While not exhaustive (e.g., default behavior if omitted), it sufficiently explains parameter intent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Analyze device partitions and mount points' with a specific verb and resource, and adds context that it is 'Essential for understanding device storage layout.' This distinguishes it from sibling tools like capture_logcat or analyze_network_connections, which focus on other subsystems.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use it ('Essential for understanding device storage layout'), implying use when storage partition information is needed. It does not explicitly exclude alternatives or name when not to use it, but the context is sufficient for a tool with unique purpose among the siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capture_dmesgA
Capture kernel ring buffer (dmesg). Contains hardware events, driver messages, and security-related logs.
Args: output_file: Path to save dmesg output device_id: Optional device serial number
Note: May require root access on some devices.
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No | ||
| output_file | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It adds meaningful information that the tool may require root access and describes the content of the captured data. However, it does not explicitly state whether the operation is read-only, potential side effects, or output handling, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a one-line summary, a brief explanation of log content, a clearly labeled args list, and a note about root access. Every sentence adds value, and the structure is front-loaded with the main purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two parameters and an output schema is present, so the description need not explain return values. It covers purpose, parameters, and a key caveat (root access). Minor gaps exist regarding when to use versus alternatives, but overall it is sufficiently complete for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no parameter descriptions (0% coverage), so the description fully compensates by explaining both parameters: output_file as the path to save dmesg output, and device_id as an optional device serial number. This is clear and actionable, though it lacks examples or format details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool captures the kernel ring buffer (dmesg) and lists the types of logs it contains (hardware events, driver messages, security-related logs). The verb 'Capture' plus the specific resource 'kernel ring buffer' makes the purpose unambiguous and distinct from sibling capture_logcat.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for kernel/hardware/security log investigation, but it does not explicitly state when to use this tool over alternatives like capture_logcat. No direct 'when to use' or 'when not to use' guidance is provided, only inferable context from the log types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capture_logcatA
Capture Android system logs (logcat). Critical for understanding device activity and app behavior.
Args: output_file: Path to save the logcat output device_id: Optional device serial number lines: Number of log lines to capture (default 10000) filter_spec: Optional logcat filter (e.g., "*:W" for warnings+) include_timestamps: Include timestamps in output
| Name | Required | Description | Default |
|---|---|---|---|
| lines | No | ||
| device_id | No | ||
| filter_spec | No | ||
| output_file | Yes | ||
| include_timestamps | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only says 'Capture Android system logs' and lists parameters; it does not mention whether the operation is safe/read-only, requires special permissions or device connection, or what side effects (e.g., overwriting output_file) might occur. This is a minimal disclosure for a tool with zero annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a one-sentence purpose, followed by an arg list where each line is necessary and informative. There is no filler, redundancy, or irrelevant detail, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, parameter semantics, and a hint of context. An output schema exists, so return values need not be explained. However, it omits environmental requirements (e.g., device connectivity, ADB presence) and potential error modes, which would be useful for a 5-parameter tool. Still, for a straightforward capture command, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description fully compensates by explaining each parameter: output_file as path, device_id as optional serial, lines with default, filter_spec with an example (%*:W% for warnings+), and include_timestamps as a boolean. This provides actionable meaning beyond the raw schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Capture Android system logs (logcat)' with a specific verb and resource, which matches the tool name and distinguishes the action. It adds context about device activity and app behavior, but it does not explicitly call out sibling tools like capture_dmesg, so it lacks direct sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Critical for understanding device activity and app behavior' provides clear use-case context, implying when an agent should reach for this tool. However, it does not explicitly state when not to use it or name alternatives, so it falls short of full explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_root_statusA
Comprehensive root/jailbreak detection. Checks multiple indicators of device rooting.
Args: device_id: Optional device serial number
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full responsibility for behavioral disclosure. It mentions 'multiple indicators' but does not disclose whether the check is read-only, requires special permissions, affects device state, or has any limitations. For a detection tool, this is insufficient operational transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core purpose. The first sentence is somewhat redundant with the tool name, but the second sentence and the Args line provide useful detail without excess. Overall, it is appropriately sized and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter) and the presence of an output schema, the description is largely complete. It explains what the tool checks and what the parameter means. It does not describe prerequisites like device connectivity or interpretation, but these are not critical for such a simple tool with structured output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates with an explicit Args section: 'device_id: Optional device serial number.' This adds meaningful semantic detail beyond the schema's bare 'Device Id' title and default null, clarifying that the parameter expects a serial number and is optional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Comprehensive root/jailbreak detection' and 'Checks multiple indicators of device rooting.' This uses a specific verb ('checks') and resource ('device rooting'), and it distinguishes the tool from siblings like extract_with_root (which performs an action using root) and other diagnostic tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description only states what the tool does, not the conditions under which it should be invoked, nor any prerequisites or exclusions. There is no mention of related tools or specific scenarios (e.g., before extract_with_root).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dump_system_settingsA
Dump all system settings (secure, system, global). Reveals device configuration, security settings, and user preferences.
Args: device_id: Optional device serial number output_file: Optional path to save results as JSON
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No | ||
| output_file | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden of disclosing behavior. It mentions that the tool 'dumps' settings and 'reveals' configuration and preferences, which implies a read-only operation, but it does not disclose potential prerequisites (e.g., root access), side effects, or any warnings about the sensitivity of the data. This is a significant gap for a tool that accesses security settings.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the primary verb and resource. It adds essential information about what is revealed and then clearly lists parameters. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a simple dump tool, but it lacks important context such as whether special permissions are required, how to interpret the output (though an output schema exists), and how it compares to related tools. Given the sensitive nature of system settings, more operational context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides zero description coverage for the two parameters, but the description compensates by explaining that device_id is an optional serial number and output_file is a path to save results as JSON. This adds meaningful semantics beyond the schema's raw parameter names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to dump all system settings (secure, system, global). It also specifies the kind of information revealed (device configuration, security settings, user preferences), which distinguishes it from sibling tools like check_root_status or get_running_processes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about what the tool does and what kind of information it reveals, implying its use for inspecting device configuration and security settings. However, it does not explicitly mention when to use it instead of alternative tools or any exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_with_rootA
Extract files using root privileges. Bypasses Android security restrictions for forensic acquisition.
Args: remote_path: Path on device (e.g., /data/data/com.whatsapp) local_path: Local destination path device_id: Optional device serial number
Warning: Requires rooted device. May trigger security alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No | ||
| local_path | Yes | ||
| remote_path | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses root requirement and potential security alerts, which is valuable. However, it doesn't describe side effects such as file permissions, whether local directories are created, or error handling, leaving some ambiguity. Credits given for the warning about security alerts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured, with purpose, arguments, and warning clearly separated. Every sentence contributes meaningful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description doesn't need to explain return values. It covers purpose, parameters, and important warnings in a concise manner. However, it lacks explicit guidance on when to prefer this tool over siblings, and the absence of annotations leaves a few behavior aspects unclear, but overall it's fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description's Args section is essential. It clearly explains each parameter, gives an example for remote_path, and marks device_id as optional. This compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb-object statement ('Extract files using root privileges') and adds contextual purpose ('Bypasses Android security restrictions for forensic acquisition'). This distinguishes it from sibling tools handling logs, packages, or processes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context for use: forensic acquisition requiring root privileges, and warns about root requirement and security alerts. However, it doesn't explicitly name alternatives or say when not to use it, so it's clear context but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_account_infoA
Get registered accounts on the device. Identifies Google, social media, and other linked accounts.
Args: device_id: Optional device serial number output_file: Optional path to save results as JSON
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No | ||
| output_file | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It reveals the type of accounts returned and the JSON-saving behavior via output_file, but does not discuss permissions, platform constraints, or behavior when no accounts exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a clear purpose statement, followed by a brief, well-structured arg list. Every sentence earns its place with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with two optional parameters and an output schema, the description covers purpose, account types, and output file semantics. It is complete for the tool's complexity, though more on result details could be added.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides meaningful explanations for both parameters: device_id as an optional serial number and output_file as an optional JSON path, going beyond the bare schema types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and identifies the exact resource ('registered accounts'), further clarified as Google, social media, and other linked accounts. This clearly distinguishes it from sibling tools like get_running_processes or dump_system_settings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It implies the tool is for enumerating accounts on a device, but provides no explicit when-to-use vs alternatives or exclusions. Sibling tools don't overlap, so the context is clear, but explicit guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_installed_packagesA
Get list of all installed packages with details. Essential for identifying installed applications.
Args: device_id: Optional device serial number include_system: Include system apps output_file: Optional path to save results as JSON
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No | ||
| output_file | No | ||
| include_system | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states the core action but omits important details such as whether the tool requires a connected device, how it behaves without device_id, or the exact content of 'details.' No side effects or prerequisites are mentioned, leaving significant transparency gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the main purpose. The parameter list is straightforward and compact. The only minor extra is 'Essential for identifying installed applications,' which adds context but could be seen as slightly redundant. Overall, it's efficient and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has an output schema and only three optional parameters, the description covers basic functionality but lacks depth. It does not explain default behavior (e.g., default device when device_id omitted) or potential side effects of writing to output_file. For a simple list tool, this is sufficient but not rich, leaving some gaps in operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description's parameter list is essential. It provides meaningful semantics for each parameter: device_id as optional serial number, include_system for system apps, and output_file for saving JSON. While brief, it clarifies the role of every parameter, adding value beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb and resource: 'Get list of all installed packages with details.' This unambiguously distinguishes it from sibling tools like get_running_processes or dump_system_settings, which target different system aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear context for use ('Essential for identifying installed applications') but does not explicitly state when to avoid this tool or mention alternatives. Usage guidance is implied rather than explicit, with no exclusions or comparisons to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_running_processesA
Get list of running processes. Identifies active applications and background services.
Args: device_id: Optional device serial number output_file: Optional path to save results as JSON
| Name | Required | Description | Default |
|---|---|---|---|
| device_id | No | ||
| output_file | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does add useful behavioral context by clarifying that 'running processes' includes active applications and background services, and it notes that output_file saves results as JSON. However, it does not disclose potential errors, device selection behavior when device_id is omitted, or any permissions required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, with a clear opening line, a helpful elaboration, and a compact args listing. Every sentence adds value and there is no redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple read-only nature of the tool, the presence of an output schema, and the adequate parameter descriptions, the description is mostly complete. It lacks usage guidelines and behavioral caveats, but these are less critical for a straightforward list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It effectively explains both parameters: device_id is a device serial number, and output_file is a path for saving JSON results. This adds meaning beyond the bare schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets a list of running processes and identifies active applications and background services. This is a specific verb+resource, but it does not explicitly distinguish from sibling tools such as get_installed_packages, though the resource 'running processes' is inherently distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like get_installed_packages or capture_logcat. There is no mention of exclusions, prerequisites, or typical use cases, so the agent must infer usage from the name and description alone.
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.
10 tool updates
v1.0.0- First observed
analyze_network_connections - First observed
analyze_partition_info - First observed
capture_dmesg - First observed
capture_logcat - First observed
check_root_status - First observed
dump_system_settings - First observed
extract_with_root - First observed
get_account_info - First observed
get_installed_packages - First observed
get_running_processes
TDQS
Each tool targets a distinct forensic data source or action: root status, logcat, dmesg, packages, settings, network, processes, file extraction, partitions, and accounts. There is no overlap; even capture_logcat and capture_dmesg are clearly differentiated as system/app logs vs kernel buffer.
All tool names follow a consistent verb_noun pattern using snake_case (check_root_status, capture_logcat, get_installed_packages, etc.). The verbs are varied but predictable, and the structure is uniform across the set.
10 tools is well-scoped for an Android forensics server, covering the major data sources without unnecessary redundancy. The count falls comfortably within the ideal 3-15 range, and each tool earns its place in the toolkit.
The set covers core forensic acquisition and analysis: device status, logs, installed apps, settings, network, processes, file extraction, partitions, and accounts. Minor gaps exist, such as dedicated tools for SMS/call logs or media files, but the generic extract_with_root can access these if the path is known, making it a workable limitation.
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