Skip to main content
Glama

Remediation Plan

remediate
Read-onlyIdempotent

Scan AI agent configurations for vulnerabilities and generate actionable fix commands, including package upgrades and credential scope reductions.

Instructions

Generate a remediation plan for vulnerabilities in your AI agent setup.

    Scans for vulnerabilities, then generates actionable fix commands for
    each affected package (npm install, pip install), credential scope
    reduction guidance, and reports on unfixable vulnerabilities.

    Args:
        config_path: Path to a specific MCP config directory.
                     If not provided, auto-discovers all local agent configs.
        image: Docker image reference to scan (e.g. "nginx:1.25").

    Returns:
        JSON with package_fixes (upgrade commands by ecosystem),
        credential_fixes (scope reduction steps), and unfixable items.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
config_pathNoPath to MCP client config directory. Auto-discovers all if omitted.
imageNoDocker image to scan, e.g. 'nginx:1.25'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description fully discloses behavior: scanning for vulnerabilities, generating fix commands (npm install, pip install), credential scope reduction guidance, and reporting unfixable items. Annotations (readOnlyHint=true) align with generating instructions without executing them.

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-structured with clear sections (purpose, scanning, arguments, returns). It is slightly lengthy but each sentence provides relevant information.

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 complexity, the description covers all necessary aspects: scanning, fix generation, optional parameters, and return structure. Together with the input and output schema, the description is fully complete.

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 coverage is 100%, and the description adds minimal value beyond the schema. It clarifies behavior for config_path (auto-discovers if omitted) and image, but this is largely repetitive.

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: generating remediation plans for vulnerabilities in AI agent setups. It specifies scanning for vulnerabilities and producing fix commands, distinguishing it from sibling tools that focus on scanning alone.

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 provides clear context on when to use the tool (after vulnerabilities are found) and describes the optional parameters (config_path, image). However, it does not explicitly mention when not to use or compare to alternative tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/msaad00/agent-bom'

If you have feedback or need assistance with the MCP directory API, please join our Discord server