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8 clients · secrets stay placeholders

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{
  "mcpServers": {
    "waveguard": {
      "type": "http",
      "url": "https://gpartin--waveguard-api-fastapi-app.modal.run/mcp"
    }
  }
}

claude mcp add --transport http waveguard https://gpartin--waveguard-api-fastapi-app.modal.run/mcp

[mcp_servers.waveguard]
url = "https://gpartin--waveguard-api-fastapi-app.modal.run/mcp"

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "waveguard": {
      "type": "remote",
      "url": "https://gpartin--waveguard-api-fastapi-app.modal.run/mcp",
      "enabled": true
    }
  }
}

{
  "mcpServers": {
    "waveguard": {
      "type": "http",
      "url": "https://gpartin--waveguard-api-fastapi-app.modal.run/mcp"
    }
  },
  "deeplink": "cursor://anysphere.cursor-deeplink/mcp/install?name=waveguard&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vZ3BhcnRpbi0td2F2ZWd1YXJkLWFwaS1mYXN0YXBpLWFwcC5tb2RhbC5ydW4vbWNwIn0%3D"
}

{
  "servers": {
    "waveguard": {
      "type": "http",
      "url": "https://gpartin--waveguard-api-fastapi-app.modal.run/mcp"
    }
  }
}

{
  "mcpServers": {
    "waveguard": {
      "httpUrl": "https://gpartin--waveguard-api-fastapi-app.modal.run/mcp"
    }
  }
}

extensions:
  "waveguard":
    enabled: true
    name: "waveguard"
    type: streamable_http
    uri: "https://gpartin--waveguard-api-fastapi-app.modal.run/mcp"
    timeout: 300

Quality 83 / 100good

protocol75 · weight 25

warn
protocol.modernnewest supported version is 2024-11-05; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
n/a
protocol.statelessonly applies to 2026-07-28 servers
pass
protocol.transportstreamable HTTP
n/a
protocol.list_ttlonly applies to 2026-07-28 servers

authorizationn/a · weight 15

n/a
auth.prm, auth.as_metadata, auth.cimdno remote uses OAuth
n/a
auth.secret_in_urlno templated URL

tool hygiene93 · weight 30

pass
tools.descriptionsevery tool has a description
warn
tools.description_length1 tools have descriptions over 1,024 characters, which crowds the context
pass
tools.schemasevery tool has an object input schema
pass
tools.annotations19 of 19 tools declare readOnlyHint or destructiveHint
pass
tools.directory_hintsevery tool declares readOnlyHint, destructiveHint, idempotentHint and openWorldHint
pass
tools.token_costabout 5,174 tokens to load every tool
pass
tools.api_dumptools are not a one-to-one API dump

stability75 · weight 15

warn
stability.changes76 tool changes in 30 days
pass
stability.rug_pullno tool changed its meaning under the same name

dependenciesn/a · weight 15

n/a
deps.known_vulns, deps.mcp_sdk_version, deps.resolvableno npm or PyPI package

19 tools, about 5,174 tokens to load them all · tool set 1a4b15abcc27 · tools last changed 2026-10-13 · checked 2026-10-19 16:53 UTC

Tool changes

2026-10-13waveguard_multi_horizon_outlookadded
Compute horizon-specific anomaly outlook and consistency across windows.
2026-10-13waveguard_action_surfaceadded
Score candidate actions and extract robust action zones.
2026-10-13waveguard_mechanism_probeadded
Run targeted interventions and rank effect sizes.
2026-10-13waveguard_cascade_riskadded
Estimate shock propagation and resilience from adjacency-linked entities.
2026-10-13waveguard_interaction_matrixadded
Compute pairwise interaction matrix and cluster decomposition for entities.
2026-10-13waveguard_phase_coherenceadded
Measure coherence/entropy and collapse-risk indicators for candidate data.
2026-10-13waveguard_instabilityadded
Estimate instability under controlled perturb-and-resolve trials.
2026-10-13waveguard_trajectory_scanadded
Analyze sequence drift and regime shifts over ordered samples.
2026-10-13waveguard_counterfactualadded
Run baseline plus counterfactual variants and measure verdict/score sensitivity.
2026-10-13waveguard_market_dataadded
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: price, volume, market cap, liquidity, price history, OHLC candles — ready to feed into waveguard_token_risk, waveguard_volume_check, or waveguard_price_manipulation.

Showing the latest 10. Full history: list_changes · trend: quality JSON.

Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.

Trust 84 / 100

provenance90

liveness92

freshness45

hygiene100

+repository +namespace-matches-repo +website +reachable +uptime-81% -stale-232d

Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. How it is computed.

Endpoints

remote	auth	reachable	uptime 30d	p50	protocol	last ok
`https://gpartin--waveguard-api-fastapi-app.modal.run/mcp` streamable-http	none	yes	81%	3996 ms	2024-11-05	2026-10-19

Tools (19)

`waveguard_action_surface`read-only	Score candidate actions and extract robust action zones.
`waveguard_cascade_risk`read-only	Estimate shock propagation and resilience from adjacency-linked entities.
`waveguard_compare`read-only	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 > 0.95 = very similar. < 0.80 = structurally different.
`waveguard_counterfactual`read-only	Run baseline plus counterfactual variants and measure verdict/score sensitivity.
`waveguard_fingerprint`read-only	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 metrics, wallet activity, trading data, or any structured data. Returns a deterministic vector with labeled dimensions (chi statistics, energy distribution, gradient patterns, and phase coherence at Level 1).
`waveguard_health`read-only	Check WaveGuard API health, GPU availability, version, and engine status. No authentication required. Returns status, version, and GPU info.
`waveguard_instability`read-only	Estimate instability under controlled perturb-and-resolve trials.
`waveguard_interaction_matrix`read-only	Compute pairwise interaction matrix and cluster decomposition for entities.
`waveguard_market_data`read-only	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: price, volume, market cap, liquidity, price history, OHLC candles — ready to feed into waveguard_token_risk, waveguard_volume_check, or waveguard_price_manipulation.
`waveguard_mechanism_probe`read-only	Run targeted interventions and rank effect sizes.
`waveguard_multi_horizon_outlook`read-only	Compute horizon-specific anomaly outlook and consistency across windows.
`waveguard_phase_coherence`read-only	Measure coherence/entropy and collapse-risk indicators for candidate data.
`waveguard_price_manipulation`read-only	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 windows.
`waveguard_scan`read-only	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 as test in ONE call. Returns per-row anomaly scores, confidence levels, and the top features explaining WHY each row was flagged. Typical workflow: (1) Pull data from another tool (e.g. Google Sheets, Supabase query, HubSpot deals). (2) Pass the first N rows as training (normal baseline). (3) Pass remaining or new rows as test. (4) Report which rows are anomalous and why. Works on JSON objects, numbers, text, arrays. No separate training step required. Examples: - Spreadsheet QA: Pull 500 sales rows from Sheets → train on first 400 → test last 100 → flag outlier entries - Financial screening: Get ratios for 50 stocks from a financial API → find anomalous ones - CRM hygiene: Pull HubSpot deals → flag deals with unusual discount/value patterns - Dependency audit: Get NPM package metrics → flag packages with anomalous quality scores - Commit review: Pull GitHub commit metadata → flag unusual commit patterns
`waveguard_scan_timeseries`read-only	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 workflow: (1) Pull a column of numbers from Sheets, a Supabase time-series table, or a metrics API. (2) Pass the array here. (3) Get back which time windows are anomalous. Examples: - Revenue monitoring: Pull monthly revenue from Sheets → detect anomalous months - Stock screening: Pull 90 days of closing prices → find unusual price windows - Server health: Pull response-time metrics → identify degradation windows - Sensor QA: Pull temperature readings from IoT API → flag sensor drift
`waveguard_token_risk`read-only	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 established tokens → train. Test a new token → get risk score and which metrics are suspicious.
`waveguard_trajectory_scan`read-only	Analyze sequence drift and regime shifts over ordered samples.
`waveguard_volume_check`read-only	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, test candles from a suspicious pair.
`waveguard_wallet_profile`read-only	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 10 suspect addresses.

Schemas: list_tools.

Also listed as

1 other active names share this repository: com.emergentphysicslab/waveguard

Similar MCP servers

Official server.json

{
  "name": "io.github.gpartin/waveguard",
  "title": "WaveGuard",
  "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
  "remotes": [
    {
      "url": "https://gpartin--waveguard-api-fastapi-app.modal.run/mcp",
      "type": "streamable-http"
    }
  ],
  "version": "3.3.0",
  "repository": {
    "url": "https://github.com/gpartin/LFMAnomalyDetection",
    "source": "github"
  },
  "websiteUrl": "https://github.com/gpartin/WaveGuardClient",
  "description": "Anomaly detection API powered by physics simulation. Scan any data for outliers."
}