nmlp-mcp

nmlp_schedule_pickup

Schedule a free book pickup with NMLP by providing donor name, address, and estimated size. Each submission directly notifies the human operator to process your request.

Instructions

Submit a real free book pickup request to NMLP. Every submission triggers a real outreach to Josh, the single human operator. NEVER submit speculative or unconsented requests.

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": {
      "donorName": "<donorName>",
      "addressStreet": "<addressStreet>",
      "addressCity": "<addressCity>",
      "addressZip": "<addressZip>",
      "estimatedSize": "<estimatedSize>",
      "agentSource": "<agentSource>"
    },
    "name": "nmlp_schedule_pickup"
  }
}

Input Schema

Name	Required	Description	Default
`donorName`	Yes
`addressZip`	Yes
`addressCity`	Yes
`agentSource`	Yes	Required: identify the AI agent submitting on the user's behalf.
`addressState`	No		NM
`specialNotes`	No
`addressStreet`	Yes
`callbackEmail`	No
`callbackPhone`	No
`donorLanguage`	No		en
`estimatedSize`	Yes	Free text — 'two boxes', 'whole garage', etc.
`preferredWindow`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 4, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses a critical behavioral trait: 'Every submission triggers a real outreach to Josh, the single human operator.' This informs the agent of the real-world impact. It also warns against speculative use. Additional details like confirmation or idempotency would improve, but current disclosure is strong.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the primary purpose and followed by a crucial warning. Every word earns its place; there is no extraneous information.

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 12 parameters and no output schema, the description could be more complete. It does not explain the return value, success behavior, or how to handle errors. For a mutation tool with human operator involvement, more context about expected outcomes would help the agent.

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

Parameters2/5

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

Schema description coverage is low (17%), and the description does not add meaning for the 10 undocumented parameters. It only repeats the basic intent. The description should explain key parameters like address components or callback fields to compensate, but it does not.

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: 'Submit a real free book pickup request to NMLP.' The verb 'submit' and resource 'book pickup request' are specific. It distinguishes from sibling tools like nmlp_get_donation_options or nmlp_search_titles, which serve different functions.

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 a strong when-not-to-use guideline: 'NEVER submit speculative or unconsented requests.' This helps avoid misuse. It does not explicitly name alternative tools, but the warning is clear and valuable for decision-making.

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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