LION Trend Intent MCP

lion_base_dex_signals_json

Live Base (eip155:8453) DEX market-data feed for trading and research agents. Returns a fresh ranked snapshot of active Base tokens with raw on-chain metrics: price_usd, liquidity_usd, volume_h24, volume_m5, price_change_h1/h24, pair_age_hours, dex, and a transparent mechanical activity_score (volume + liquidity + recency). Source: public DexScreener data, no API key. Raw public market data only - not financial or investment advice, no buy/sell recommendation. Pay 0.005 USDC on Base via x402 at the paid route. tools/call returns payment-required metadata only; settle the x402 invoice at the paid route to fetch the live JSON.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description discloses data source, payment requirement, return flow, and mechanical scoring. It omits rate limits or pagination but adequately warns about financial advisory limitations.

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?

Well-structured with purpose, metrics, source, disclaimer, and payment. Could be slightly shorter but every sentence adds value.

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 zero parameters and no output schema, the description covers what the tool returns, how to access it, and source context. Does not specify snapshot size limits or update frequency, but sufficient for a live feed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters, so baseline 4. Description adds no parameter info needed.

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 is a live DEX market-data feed for Base chain, returning ranked snapshots with specific metrics. It distinguishes from sibling tools that focus on trend intent signals.

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?

Describes payment flow and that data is raw market data, not financial advice. However, it does not explicitly differentiate when to use this tool vs siblings like lion_trend_intent_signal_json, leaving usage context implied.

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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TDQS

A4.1/5.0

Disambiguation2/5

The adaptive_data_query tool overlaps with base_dex_signals_json by offering DEX data, and the two trend_intent_signal tools differ only in format (CSV vs JSON), causing ambiguity about which tool to use. The payment audit tool is distinct, but overall the boundaries are unclear.

Naming Consistency4/5

All tools use a consistent 'lion_' prefix and snake_case. However, some tools specify the output format (e.g., '_json', '_csv') while others do not (e.g., 'adaptive_data_query'), creating minor inconsistency. Overall, the pattern is predictable.

Tool Count5/5

With 5 tools covering data queries, DEX signals, payment readiness, and trend signals, the count is well-scoped for the server's purpose. Each tool serves a clear function without excessive redundancy in number.

Completeness4/5

The tool set covers the main use cases: general on-chain data querying, dedicated DEX signals, payment term audits, and trend intent signals. The redundancy between adaptive_data_query and base_dex_signals_json, and the two trend signal formats, is minor. No major gaps are apparent.

Resources

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