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remove_server

Destructive

Remove an MCP server from your AI client's configuration by specifying the server name. Supports removing from multiple clients at once.

Instructions

Remove an MCP server from your AI client's configuration.

Removes the server entry from the config file. The user must restart their MCP client for the change to take effect.

Use list_installed to see server names. Use clients="all" to remove from every configured client at once.

Args: server_name: Exact name of the server to remove, as shown by list_installed. clients: Target MCP client(s). Comma-separated names like "claude_desktop,cursor", "all" for every detected client, or empty to auto-detect. scope: "user" for global config (default), "project" for project-scoped config. project_path: Project directory path. Required when scope="project".

Returns: Result with success status and message. Multi-client calls also include per_client_results with per-client removal status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
server_nameYes
clientsNo
scopeNouser
project_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The annotation destructiveHint=true already flags destruction. The description adds the behavioral detail that the user must restart the client for changes to take effect, which is valuable beyond the annotation.

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?

Well-structured with clear sections and bullet-like Args. Every sentence adds value, but could be slightly more concise. Still earns its place.

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?

With an output schema present, the description still explains return values (success status, per_client_results). It covers all necessary context for a removal tool, including restart requirement.

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?

With 0% schema description coverage, the description fully explains each parameter: server_name (exact name), clients (comma-separated, 'all', or auto-detect), scope ('user' default vs 'project'), project_path (required for project scope). Also describes return values.

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 it removes an MCP server from AI client configuration, using specific verb 'remove' and resource 'MCP server from AI client's configuration'. It distinguishes from siblings like configure_server, inspect_server, and list_installed.

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?

Provides explicit usage context: suggests using list_installed to see server names, explains clients parameter with 'all' option. While it doesn't explicitly say when not to use, the context is clear and helpful.

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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