gapup-mcp

crypto_wallet_intel

Read-only

Multi-chain on-chain analytics for crypto trading agents, on-chain analysts, AML/compliance teams and DeFi BD. Covers Ethereum, Base, Polygon, BSC, Arbitrum, Optimism — EVM-compatible addresses only.

5 modes: • wallet_profile — full wallet summary: type (EOA/contract/CEX/protocol), inferred persona (whale/MEV-bot/DeFi-user/hodler…), age, tx count, native balance, ERC-20 count, NFT collections, OFAC sanctions flag • token_flows — ERC-20 inflows/outflows per token on the selected period, priced in USD via CoinGecko • pnl_estimate — FIFO realized + unrealized P&L on the period with confidence rating (high/medium/low) • counterparties — top 20 counterparties ranked by USD volume with CEX/DEX/protocol labels • defi_positions — active DeFi positions detected via Etherscan interaction history (Aave/Compound/Uniswap/Curve/Lido/Balancer/SushiSwap)

Signal detection (P0/P1/P2): P0 if OFAC SDN match OR direct Tornado Cash / sanctioned-protocol interaction P1 if >$1M volume on wallet <30 days old OR MEV-bot pattern OR >80% volume on single counterparty P2 informational (CEX wallet, new wallet, no anomaly)

Sources: Etherscan family (keyless free-tier, optional API key per chain), DefiLlama (keyless), public EVM RPC (keyless), CoinGecko free tier (keyless). Cache TTL: 5 min (wallet activity evolves fast). Budget: 8s per source.

Env vars (all optional, raise Etherscan rate-limit from 1 req/5s to 5 req/s): ETHERSCAN_API_KEY · BASESCAN_API_KEY · POLYGONSCAN_API_KEY BSCSCAN_API_KEY · ARBISCAN_API_KEY · OPTIMISM_API_KEY

Input Schema

TableJSON Schema

Name	Required	Description
`mode`	Yes	Analysis mode. wallet_profile=full wallet summary + persona + sanctions flag. token_flows=ERC-20 inflows/outflows per token priced in USD. pnl_estimate=FIFO realized+unrealized P&L with confidence. counterparties=top 20 counterparties by volume. defi_positions=active positions on Aave/Compound/Uniswap/Curve/Lido/etc.
`async`	No	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
`chain`	No	Chain to analyze. Default "ethereum". Use "all" to scan all 6 chains (slower, ~30s).
`address`	Yes	EVM-compatible wallet address (0x... 40 hex chars). Works on all supported chains.
`period_days`	No	Lookback window in days for token_flows, pnl_estimate, counterparties, defi_positions. Default 30.
`min_value_usd`	No	Minimum USD value filter for token_flows and counterparties. Default $100.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`mode`	Yes
`status`	Yes
`address`	Yes
`signals`	Yes
`sources`	Yes
`token_flows`	No
`pnl_estimate`	No
`quality_score`	Yes
`counterparties`	No
`defi_positions`	No
`wallet_profile`	No
`chains_analyzed`	Yes

TDQS

A4.5/5.0

Behavior5/5

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

The description details read-only nature (consistent with readOnlyHint=true), multi-source dependency, caching, performance budgets, and env vars for rate limits. It adds significant behavioral context beyond annotations.

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 well-structured with an overview, bullet list of modes, signal detection, sources, caching, and env vars. Every sentence adds value without redundancy, achieving conciseness despite length.

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

Completeness5/5

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

Given the tool's complexity (6 parameters, 5 modes, signal levels, env vars), the description covers all major aspects: input details, behavioral traits, source dependencies, caching, and performance budget. The existence of an output schema (not shown) compensates for missing return value details.

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?

The schema covers all parameters with descriptions. The description adds value by explaining mode-specific details (signal detection, P0/P1/P2 levels) that aren't in the schema, though other parameters like period_days are well-documented in schema.

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's purpose: multi-chain on-chain analytics for crypto trading agents, analysts, AML, and DeFi teams. It lists 5 distinct modes and supported chains, distinguishing it from siblings like usdc_x402_payments_intel.

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 provides extensive context on what the tool does but does not explicitly state when to use it versus alternatives. No 'use this when' or exclusion criteria are given, relying on the specificity of the tool to imply usage.

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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources

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