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bca-mcp

bca-mcp

by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_article

Retrieve the complete text of a crypto editorial article by its slug, including citations, entity graph, and attribution metadata. Use this to access full content after finding an article slug via search.

Instructions

Fetch a single editorial crypto article by slug: full body, citations, entity graph, and attribution metadata. Required field: 'slug'. Use after search_news when you need the full text of a specific result.

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": {
      "slug": "<slug>"
    },
    "name": "get_article"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesArticle slug (e.g. 'circle-ipo-pricing-2026-04').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It correctly implies a read operation but does not mention authentication requirements, rate limits, or error handling (e.g., behavior when slug is invalid). For a simple fetch, the lack of detail is acceptable but not exemplary.

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?

Two sentences front-load the action and return information, then provide usage guidance. Efficient and clearly structured, with no extraneous text.

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?

Given the tool's simplicity (one parameter, no output schema), the description covers purpose, input, and usage context. It does not mention failure modes or error handling, but for a low-complexity tool this is minor. Could be improved by stating it returns null or error on missing slug.

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?

Schema coverage is 100% with a well-described 'slug' parameter including an example. The description repeats 'Required field: slug' which adds no value beyond the schema. Baseline is 3 due to high schema coverage.

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 it fetches an editorial crypto article by slug and lists the returned data components (full body, citations, entity graph, attribution metadata). This specificity differentiates it from siblings like search_news and get_editorial_premium.

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

Usage Guidelines5/5

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

Explicitly instructs 'Use after search_news when you need the full text of a specific result,' providing direct guidance on when and how to use the tool versus alternatives.

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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