Skip to main content
Glama

install_packages

Install Python packages via pip with configurable options including upgrade, dependency handling, custom indexes, pre-releases, output limit, and timeout.

Instructions

Install Python packages using pip.

Parameters

packages : list of str List of package specifiers (e.g., "scikit-image", "torch==2.3.1"). upgrade : bool, optional If True, pass --upgrade flag. no_deps : bool, optional If True, pass --no-deps flag. index_url : str, optional Custom index URL. extra_index_url : str, optional Extra index URL. pre : bool, optional Allow pre-releases (--pre flag). line_limit : int, default=30 Maximum number of output lines to return. Use -1 for unlimited output. timeout : int, default=240 Timeout for pip install in seconds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packagesYes
upgradeNo
no_depsNo
index_urlNo
extra_index_urlNo
preNo
line_limitNo
timeoutNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The description details parameters like upgrade and no_deps, which hint at side effects, but it does not explicitly state that the tool modifies the Python environment, requires network access, or may have other behavioral traits. With no annotations, this is adequate but not thorough.

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 front-loaded with a clear purpose statement and uses a clean parameters section. It is structured well but slightly verbose, with each parameter having a full sentence. It earns its place but could be more concise.

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?

Given the tool has 8 parameters and an output schema (not shown), the description covers parameter semantics well but lacks behavioral context such as prerequisites, side effects, or error scenarios. It is sufficient for basic use but incomplete for advanced understanding.

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?

The input schema has 0% description coverage, so the description carries the full burden. It provides detailed explanations for all 8 parameters, including examples for packages, defaults, and flag mappings (e.g., '--upgrade flag'). 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 begins with 'Install Python packages using pip,' clearly stating the action (install) and resource (Python packages via pip). This is specific and distinguishes the tool from sibling tools that deal with viewer layers, code execution, etc.

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 provides no guidance on when to use this tool versus alternatives, such as using execute_code for more flexible installation or other package managers. It only describes what the tool does.

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/royerlab/napari-mcp'

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