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shigechika

jquants-mcp

by shigechika

register_api_key

DestructiveIdempotent

Register or update your J-Quants API key to enable stock market data retrieval. Your key is encrypted and associated with your OAuth identity.

Instructions

Register or update your J-Quants API key (multi-user mode).

⚠️ SECURITY WARNING: The API key is transmitted in plaintext via the MCP protocol and may be logged by the MCP client or LLM provider. Use the browser-based /settings page instead for secure key registration.

Stores your J-Quants API key encrypted in the server's user database, associated with your OAuth identity. The server probes plan-specific J-Quants endpoints to auto-detect the plan (free / light / standard / premium) and stores it alongside the key. Subsequent tool calls will automatically use this key and the detected plan's rate limits and date-range restrictions.

This tool requires OAuth 2.1 authentication and server-side encryption (MCP_ENCRYPTION_KEY) to be configured.

Args: api_key: Your J-Quants API key (refresh token from the J-Quants portal).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

The description discloses key behavioral traits beyond annotations: plaintext transmission, encryption, plan auto-detection, and impact on future tool calls. This adds significant context that annotations (destructiveHint, idempotentHint) do not cover, with no contradictions.

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 well-structured with a security warning, explanation, prerequisites, and args. It is front-loaded and each sentence contributes value. Some redundancy could be trimmed, but overall it is concise for the complexity.

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?

The description covers the entire context: purpose, security, prerequisites, process, and implications for subsequent tool usage. Given the tool's complexity (security, plan detection), it is complete and leaves no major gaps.

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

Parameters4/5

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

With 0% schema description coverage, the description provides a meaningful description for the sole parameter 'api_key', explaining it's a refresh token from the J-Quants portal. This adds value beyond the schema, though slightly more detail (e.g., format) could be provided.

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 that the tool registers or updates a J-Quants API key, explaining the multi-user mode and the process of storing and associating the key with OAuth identity. It effectively differentiates from sibling tools, which are all data retrieval tools.

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 explicitly states when to use the tool (to register/update API key) and provides a security warning suggesting an alternative method (browser-based /settings page). It lists prerequisites but does not explicitly compare to sibling tools, though the context is clear.

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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