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paperclip-mcp

paperclip-mcp

by shanewiseman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Install a plugin

pc_post_plugins_install

Install a plugin to your Paperclip instance by providing its package name. Optionally specify a version or indicate a local path.

Instructions

Install a plugin

Paperclip operation: POST /api/plugins/install. Authorization class: instance_admin.

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": {
      "body": "<body>"
    },
    "name": "pc_post_plugins_install"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyYes

Output Schema

NameRequiredDescriptionDefault
bodyYes
headersYes
encodingYes
status_codeYes
content_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

Annotations provide basic hints (non-readonly, non-destructive, non-idempotent, open-world), but the description does not add meaningful behavioral context beyond the API endpoint. It omits details about installation process, side effects, or what constitutes a successful installation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, but it sacrifices necessary information. It could add parameter explanations or usage context without becoming overly verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and annotations, the description still fails to cover key aspects like installation behavior, error conditions, or relationship to sibling tools. It is incomplete for an AI agent to use reliably.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description provides no explanation of parameters (packageName, version, isLocalPath). An agent would not know what values to provide or their semantics, making this a critical gap.

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 'Install a plugin' with a specific verb and resource, and distinguishes from sibling tools by providing the API endpoint and auth class. The purpose is unambiguous.

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 mentions 'Authorization class: instance_admin' which hints at when to use, but it lacks explicit guidance on when to use this tool versus alternative plugin tools like enable, disable, or upgrade. No context about prerequisites or consequences.

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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