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@blockchainacademics/mcp

@blockchainacademics/mcp

Official
by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_history_correlation

Calculate correlation series between two symbols using price or sentiment data to identify pair trade opportunities.

Instructions

Correlation series between two symbols (price/sentiment). Useful for pair trades.

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": {
      "symbol": "<symbol>",
      "peer": "<peer>"
    },
    "name": "get_history_correlation"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNo
peerYesPeer symbol to correlate against.
symbolYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It does not mention whether the tool is read-only, requires authentication, has rate limits, or any side effects. The description is minimal and does not compensate for missing annotations.

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 very concise, consisting of two sentences that front-load the core purpose. There is no fluff, but the brevity comes at the cost of missing important parameter and output details. It earns a 4 because it is efficient despite the gaps.

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

Completeness2/5

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

Given the tool's complexity (3 parameters, no output schema), the description is incomplete. It does not describe the output format (e.g., time series of correlation values), the metric used (Pearson vs. Spearman), or the interpretation of the correlation. The agent lacks sufficient context to fully understand the tool's behavior.

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 33% (only 'peer' has a description). The tool description adds no parameter details beyond the schema; 'days' remains undocumented, and 'symbol' lacks any description. With low coverage, the description should compensate but fails to explain the meaning or usage of parameters.

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 states 'Correlation series between two symbols (price/sentiment)' which clearly indicates the tool computes correlation over time. It distinguishes itself from sibling history tools (e.g., get_history_prices, get_history_sentiment) by focusing on correlation. However, the phrase '(price/sentiment)' is ambiguous whether it correlates price and sentiment or correlates the same metric across two symbols.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'Useful for pair trades,' which provides a usage context but does not offer explicit when-to-use or when-not-to-use guidance. It does not compare with sibling tools like get_pair_data or get_history_prices, leaving the agent to infer usage from the name.

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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