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bca-mcp

bca-mcp

by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

track_narrative

Monitor real-time narrative strength for crypto sectors like AI agents, RWA, DePIN, and more. Select a narrative and time window for a composite strength score.

Instructions

Real-time narrative strength (AI agents, RWA, DePIN, modular, memes, Bitcoin L2s, SocialFi, GameFi). Composite of BCA Narrative Strength Score. Starter tier.

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": {
      "narrative": "<narrative>"
    },
    "name": "track_narrative"
  }
}

Input Schema

NameRequiredDescriptionDefault
narrativeYese.g. 'ai-agents', 'rwa', 'depin', 'modular'.
windowNo7d

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description implies a read-only query but does not explicitly state it. It discloses that the score is a composite (BCA Narrative Strength Score) and that it is 'Starter tier', but does not mention side effects, rate limits, or authorization needs.

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 very concise with two succinct sentences, front-loading the key purpose. Every sentence adds value without unnecessary detail.

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?

While the description gives a high-level purpose, it does not explain what the output looks like (no output schema) or explicitly list which narratives are supported. The examples in the description and schema help, but the lack of return format information limits completeness for a simple query 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 description adds context for the 'narrative' parameter by listing multiple examples beyond the schema's single example, but it does not mention the 'window' parameter. Since schema description coverage is 50%, the description partially compensates but is insufficient to fully cover parameter meaning.

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 clearly states it tracks 'real-time narrative strength' for specific narratives (AI agents, RWA, etc.) and mentions it's a composite score. However, it does not differentiate from the sibling tool 'get_narrative_strength', leaving ambiguity about their relationship.

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 is provided on when to use this tool versus alternatives like 'get_narrative_strength' or when not to use it. The description lacks context for appropriate usage scenarios.

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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