bots.st/waveguard
WaveGuard
Detect anomalies using physics-inspired simulation
7053 ms
answered our call
- State
- Answered
- Protocol
- MCP 2024-11-05
- Tools listed
- 19
- Answered
- 3 of the last 4 calls
How to reach it
- MCP, HTTP
https://gpartin--waveguard-api-fastapi-app.modal.run/v2/mcp
What it can do
| Tool | What it says it does |
|---|---|
waveguard_action_surface | Score candidate actions and extract robust action zones. |
waveguard_cascade_risk | Estimate shock propagation and resilience from adjacency-linked entities. |
waveguard_compare | Compare two data items for structural similarity using physics-based fingerprints. Returns cosine similarity (0–1) and Euclidean distance. Use for duplicate detection, behavioral matching, drift analysis, or checking if two tokens/wallets/contracts are structurally similar. Cosine similarity >… |
waveguard_counterfactual | Run baseline plus counterfactual variants and measure verdict/score sensitivity. |
waveguard_fingerprint | Get a physics embedding of any data item (52-dim at Level 0, 62-dim at Level 1 with phase statistics). The fingerprint captures structural properties via wave-equation dynamics — useful for similarity search, clustering, baseline comparison, and drift detection. Works on JSON objects, token… |
waveguard_health | Check WaveGuard API health, GPU availability, version, and engine status. No authentication required. Returns status, version, and GPU info. |
waveguard_instability | Estimate instability under controlled perturb-and-resolve trials. |
waveguard_interaction_matrix | Compute pairwise interaction matrix and cluster decomposition for entities. |
waveguard_market_data | Fetch live crypto market data from CoinGecko and DexScreener. No external data needed — WaveGuard pulls it for you. Use 'coin_id' for CoinGecko (e.g. 'bitcoin', 'ethereum', 'solana'). Use 'contract_address' for DexScreener (any chain). Use 'search' to find token IDs by name/symbol. Returns… |
waveguard_mechanism_probe | Run targeted interventions and rank effect sizes. |
waveguard_multi_horizon_outlook | Compute horizon-specific anomaly outlook and consistency across windows. |
waveguard_phase_coherence | Measure coherence/entropy and collapse-risk indicators for candidate data. |
waveguard_price_manipulation | Detect price manipulation in time-series data. Send a price or price+volume history as a numeric array. Early windows define 'normal' trading, recent windows are tested for manipulation patterns (pump-and-dump, spoofing, layering). Example: Send 90 days of closing prices → detect manipulated… |
waveguard_scan | Find outliers and anomalies in structured data — ideal as a second step after pulling records from Google Sheets, Airtable, Supabase, Notion databases, HubSpot, Financial APIs, GitHub, NPM, or any source that returns rows of JSON. Fully stateless: send known-good rows as training and suspect rows… |
waveguard_scan_timeseries | Detect anomalies in time-series data — use after pulling numeric metrics from monitoring APIs, financial data sources, IoT sensors, or spreadsheet columns. Send a single numeric array and specify a window size. Early windows define 'normal', recent windows are tested for anomalies. Typical… |
waveguard_token_risk | Assess crypto token legitimacy risk. Send metrics from known-good tokens as training (price, volume, holders, liquidity, market_cap, age_days, etc.) and suspect tokens as test. Detects pump-and-dump patterns, fake metrics, and anomalous token profiles. Example: Pull CoinGecko data for 20… |
waveguard_trajectory_scan | Analyze sequence drift and regime shifts over ordered samples. |
waveguard_volume_check | Detect wash trading and fake volume in OHLCV candle data. Send known-legitimate candles as training and suspect candles as test. Detects artificial volume spikes, suspiciously regular patterns, and manipulated price-volume relationships. Example: Send 100 candles from a liquid pair as baseline… |
waveguard_wallet_profile | Profile wallet behavior against baselines. Send normal wallet transaction patterns as training (tx_count, avg_value, unique_tokens, gas_spent, active_days, etc.) and suspect wallets as test. Detects bot activity, wash trading wallets, and sybil patterns. Example: Profile 50 organic wallets → test… |
In its maker's words
Anomaly detection API powered by physics simulation. Scan any data for outliers.
- Website
- github.com/gpartin/WaveGuardClient
- Source
- github.com/gpartin/LFMAnomalyDetection
- Publisher
- emergentphysicslab.com
- Listed from
- the official MCP Registry as
com.emergentphysicslab/waveguard - Version
- 3.1.0, updated 26 Feb 2026
- Kinds of work
- AI models and agent tools, Security and trust, Health and science
The domain it lives on
- modal.run
- registered 31 Aug 2021 (5 years ago), at Porkbun LLC, its name does not resolve now
- github.com
- registered 9 Oct 2007 (19 years ago), at MarkMonitor Inc., its home page is a working site
From our own crawl of domain names: registry records and the home page as our crawler last saw it.
Every call we made
| When | What happened | Time |
|---|---|---|
| Answered | 7053 ms | |
| No answer in 15 s | ||
| Answered | 4803 ms | |
| Answered | 4803 ms |
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