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venv-mcp-server

venv-mcp-server

by sparfenyuk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

remove_package

Remove a package from pyproject.toml and update the associated virtual environment. Specify if it's a development dependency.

Instructions

Remove package from pyproject.toml file and update the virtual environment. Returns True if successful.

Args: package_name: Name of the package to remove. dev: If True, remove the package from the development dependency group

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "package_name": "<package_name>",
      "dev": "<dev>",
      "current_working_dir": "<current_working_dir>"
    },
    "name": "remove_package"
  }
}

Input Schema

NameRequiredDescriptionDefault
package_nameYes
devYes
current_working_dirYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description must fully convey behavioral traits. It mentions returning True on success but omits error handling, side effects (e.g., uninstalling the package), permissions, or behavior when the package is not found. The description is too sparse for a mutation tool.

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 concise with a clear main sentence and a brief parameter list. It is front-loaded with the purpose and avoids unnecessary details, though the parameter descriptions could be integrated more smoothly.

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?

The description explains the return value and basic effect (removal from pyproject.toml and virtual environment), but lacks details on the full process (e.g., whether the package is uninstalled from the environment) and does not describe 'current_working_dir'. Given no output schema, more context on behavior and prerequisites would improve completeness.

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 description coverage is 0%. The description adds meaning for 'package_name' (name of package) and 'dev' (removal from dev group) but does not describe the required 'current_working_dir' parameter. This leaves a significant gap for a required parameter.

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 action: 'Remove package from pyproject.toml file and update the virtual environment.' It distinguishes from sibling tools like 'add_package' and 'add_packages' by being the removal counterpart, making the purpose unambiguous.

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?

The description implies usage for removing a package but does not explicitly state when to use this tool versus alternatives like 'add_package' or 'sync'. No prerequisites or exclusions are mentioned, leaving the agent to infer context.

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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