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BlockRunAI

BlockRun MCP

Official
by BlockRunAI

blockrun_dex

Search real-time DEX data across multiple chains to find token prices, liquidity, trading volume, and price changes using token name, symbol, or address.

Instructions

Get real-time DEX data from DexScreener. FREE - no payment required.

Use for:

  • Token prices and liquidity across chains

  • Trading volume and price changes

  • Finding token pairs and contracts

Examples: blockrun_dex({ query: "SOL" }) -> Search for SOL pairs blockrun_dex({ token: "So11...xxx" }) -> Get specific token data blockrun_dex({ symbol: "PEPE" }) -> Search by symbol

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoSearch query (token name, symbol, or address)
tokenNoToken address for direct lookup
symbolNoToken symbol to search
chainNoFilter by chain (ethereum, solana, base, etc.)
Behavior3/5

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

No annotations are provided, so the description must bear the full burden. It mentions 'real-time' and 'FREE - no payment required', but does not disclose whether the operation is read-only, any rate limits, authentication requirements, or potential side effects. The read-only nature is implied but not explicit.

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 concise, starting with the main purpose, followed by a bullet list of use cases, and then code examples. It is well-structured and front-loaded. Minor redundancy in repeating the same examples for each parameter could be tightened.

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 4 parameters and no output schema, the description provides a good overview and usage context, but lacks details about the return format or response structure. An agent would need to infer what data fields are returned, which is a gap for a data retrieval tool.

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 input schema covers all 4 parameters with descriptions (100% coverage). The description adds value by showing example usage patterns (e.g., { query: 'SOL' }) but does not introduce new parameter meaning beyond what the schema provides. Baseline 3 is appropriate.

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 'Get real-time DEX data from DexScreener', specifying the verb (Get), resource (DEX data), and source. It provides distinct use cases (token prices, liquidity, volume) and examples that differentiate it from siblings like blockrun_price.

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 lists explicit use cases ('Use for: Token prices and liquidity across chains...') and provides concrete examples. However, it lacks explicit guidance on when not to use this tool versus alternatives, such as for simple price checks via blockrun_price.

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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