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bca-mcp

bca-mcp

by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_sentiment

Retrieve the BCA editorial sentiment bucket (bullish, bearish, neutral, mixed) for a given entity, including key drivers. Provide the entity slug to get sentiment analysis within a specified rolling window.

Instructions

BCA editorial sentiment bucket (bullish/bearish/neutral/mixed) for an entity with bucket drivers.

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": {
      "entity_slug": "<entity_slug>"
    },
    "name": "get_sentiment"
  }
}

Input Schema

NameRequiredDescriptionDefault
entity_slugYesEntity slug.
windowNoRolling window.7d

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states it returns a sentiment bucket and mentions 'bucket drivers', but provides no information about safety, idempotency, auth requirements, or other behavioral traits. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, 14 words, front-loaded with the key purpose. No extraneous information; every word earns its place.

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 the tool has 2 parameters, no output schema, and no annotations, the description does not explain what 'bucket drivers' are or the structure of the response. It is adequate but lacks detail that could further aid an agent.

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 description coverage is 100%, with clear descriptions for both 'entity_slug' and 'window' parameters. The description adds no additional meaning beyond the schema; 'rolling window' is already stated. 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 the tool retrieves 'BCA editorial sentiment bucket' for an entity, specifying the possible values (bullish/bearish/neutral/mixed) and mentioning 'bucket drivers' to indicate additional detail. This distinguishes it from siblings like 'get_sentiment_velocity'.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. The sibling list includes 'get_sentiment_velocity' and other sentiment-related tools, but the description does not differentiate usage contexts or provide when-not-to-use criteria.

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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