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BlockRunAI

BlockRun MCP

Official
by BlockRunAI

blockrun_price

Retrieve real-time quotes and OHLC history for crypto, forex, commodities, and global stocks using Pyth data.

Instructions

Realtime quotes and OHLC history for crypto, FX, commodities and 12 global stock markets (Pyth-backed).

  • action="price" — realtime quote for a symbol

  • action="history" — OHLC bars between from/to (unix seconds)

  • action="list" — discovery: list available symbols (free)

Pricing:

  • crypto / fx / commodity: FREE across price, history and list

  • stocks / usstock: $0.001 per price or history call (list free)

Stocks markets: us, hk, jp, kr, gb, de, fr, nl, ie, lu, cn, ca (required when category="stocks").

Examples:

  • { action: "price", category: "crypto", symbol: "BTC-USD" }

  • { action: "price", category: "stocks", symbol: "AAPL", market: "us" }

  • { action: "history", category: "crypto", symbol: "ETH-USD", resolution: "D", from: 1700000000, to: 1710000000 }

  • { action: "list", category: "crypto", query: "sol" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesWhich endpoint to hit: price, history, or list.
categoryYesMarket category.
symbolNoTicker (required for price+history). e.g. BTC-USD, AAPL, EUR-USD.
marketNoStock market code — required when category='stocks'.
sessionNoEquity session hint (pre/post/on); ignored for non-equity.
resolutionNoBar resolution for history (default D).
fromNoHistory window start (unix seconds).
toNoHistory window end (unix seconds).
queryNoFree-text filter for list.
limitNoMax items for list (default 100, max 2000).
agent_idNoAgent identifier for budget tracking and enforcement.
Behavior3/5

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

Since no annotations are provided, the description must convey behavioral traits. It covers pricing conditions and the need for market when category='stocks'. However, it does not mention error handling, rate limits, or what happens if a symbol is not found. The examples help but lack details on edge cases.

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 well-structured using bullet points and clear sections. It is concise enough to be quickly parsed, yet includes all essential information (actions, pricing, examples). Every sentence contributes to understanding how to use the tool.

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

Completeness4/5

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

The description effectively explains how to invoke the tool and the logic behind parameters, but it lacks details about the output format (e.g., what fields are returned for 'price' or 'history'). Without an output schema, the description should at least mention the structure of the response for completeness.

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?

The input schema covers 100% of parameters with descriptions and enums. The description adds value by providing concrete examples for each action, clarifying when parameters are required (e.g., market for stocks), and explaining the meaning of action, resolution, and other fields beyond the schema's basic text.

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 provides realtime quotes and OHLC history for multiple asset classes (crypto, FX, commodities, stocks) backed by Pyth. It defines three distinct actions (price, history, list) and differentiates from other blockrun tools that have different domains (chat, dex, search, etc.).

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 explains when to use the 'price,' 'history,' and 'list' actions, and includes pricing details (free vs. paid) and required fields like market for stocks. It does not explicitly state when not to use the tool or suggest alternatives, but the sibling tools are very different, so this is acceptable.

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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