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datafood-mcp

by io.github.atmflow55
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datafood_portfolio_ask

Natural-language Q&A on a Plaid-linked portfolio (read-only). Requires user_id of a previously-synced portfolio.

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": {
      "user_id": "<user_id>",
      "question": "<question>"
    },
    "name": "datafood_portfolio_ask"
  }
}

Input Schema

NameRequiredDescriptionDefault
user_idYes
questionYese.g. 'Am I overexposed to tech?'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

The description discloses that the tool is read-only and requires a previously-synced portfolio user_id, which are useful behavioral traits. However, with no annotations, it does not cover error behavior, data freshness, or invalid user_id handling, limiting transparency.

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 extremely concise: two sentences, front-loaded with the core purpose and followed by the key prerequisite. No redundant 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?

For a simple read-only Q&A tool, the description covers purpose, safety, and a parameter prerequisite. However, it does not mention the return format or provide guidance on choosing this tool over siblings, leaving gaps for agent selection.

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?

The description adds context for user_id by specifying it must belong to a previously-synced portfolio, partially compensating for the schema lacking a description for that parameter. The question parameter already has an example in the schema, and the description does not add further meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs natural-language Q&A on a Plaid-linked portfolio and is read-only. It identifies the specific resource and action but does not explicitly differentiate it from sibling tools like datafood_query or datafood_bundle.

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 a prerequisite (user_id of a previously-synced portfolio) but no guidance on when to use this tool versus siblings. There is no when-not-to-use or alternative recommendation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All datafood-mcp toolsInspect
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