ZBS Index What actually exists in applied AI, with the source next to it

mcp server

Seiche — funding-stress terminal

Funding stress early warning for US money markets from free public data, with an honest backtest.

Description as published by the maintainer. Source

  • version 0.8.0
  • active

active — Most recent push to the repository was 2026-08-06.

What this server can do

8 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

crypto_stress_record
Labelled crypto stress episodes (Black Thursday 2020, Terra, FTX, the SVB/USDC weekend, the Oct-2025 liquidation cascade, the Ethena unwind) replayed with causal truncation but final/current-vintage inputs against the dollar-funding board. External wrecks show transmission; crypto-native wrecks show the board correctly staying quiet. Use for any 'does TradFi funding stress reach crypto' question, grounded in the record.
data_health
Freshness, provenance, and fault status for every underlying series (FRED, NY Fed, OFR, Treasury). Call this to confirm the board is current before relying on a reading.
funding_stress_now
The live money-market funding-stress reading: a 0-100 composite index, the regime (CALM/EROSION/STRAIN/STRESS), per-component decomposition, the market-stress 'Tell', and any data faults. Ask this whenever an analysis touches US dollar funding, repo, reserves, the Fed's balance sheet, or liquidity conditions.
fx_materials_passage
The live upstream FX and physical-material pressure read versus funding already priced in SOFR and commercial paper, with the Passage's discovery/holdout ledger, de-clustered analogs, dollar-system context and settlement scenarios. Use for currency weakness, commodity working capital, FX settlement, or whether trade-flow cash pressure is reaching money markets. Context only; an earned link is stable association, not causation.
historical_analogs
The historical days most similar to today's funding conditions, and how often those analogs led to a stress event, plus a novelty flag for whether today has any close precedent. Use to ground a 'what usually happens from here' question in real history.
institutional_flows
Hedge-fund / pension / sovereign positioning nowcast from public prints: the Treasury basis-trade size proxy (CFTC leveraged-fund net short, with a funding-fragility flag), asset-manager duration demand, foreign-official custody flows (H.4.1), a mixed-frequency fused positioning index with uncertainty bands, and how self-exciting stress events currently are (Hawkes branching ratio). Weekly cadence, point-in-time. Ask this when a question involves hedge fund leverage, the basis trade, pension duration bids, or sovereigns buying/selling Treasuries. Built from free public data.
oil_funding_context
Observed WTI/Brent, commercial-paper and SOFR−IORB evidence; Ballast's WTI/Henry Hub CFTC positioning, gross mark-displacement proxy, paying-side concentration and EIA inventory ledger; live Cushing stocks and the Brent−WTI spread kept separate from dated capacity, benchmark and chokepoint references; the change-on-change oil/CP association; plus explicitly scenario-only cargo-credit, margin and India cash arithmetic. Use when a question asks how oil or energy futures can transmit cash pressure into dollar funding. Ballast is not an observed margin call; dated structure is not live transit data; nothing here is a forecast, trade signal, or Seiche composite input.
proof_backtest
The backtest scoreboard, stated honestly: recall and precision with 95% confidence intervals over labelled funding events, an orthogonal robustness test, every named episode (hits and misses), and the caveats. Use to judge how much to trust the readings.

Last successful function declaration observed on . Source: https://api.seiche.info/mcp. We list what the server declared; we do not call any of these functions.

Endpoint status observed on . Source: https://api.seiche.info/mcp.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Signal Value What it measures Window Observed Source
GitHub stars 0 Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. cumulative, all time GitHub
Last commit 2026-08-06 Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. point in time GitHub
Open issues 1 Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. as of fetch GitHub
Latest published version 0.8.0 Latest version string the maintainer published to the registry. as of fetch Model Context Protocol
Registry record last updated 2026-08-02 When the registry record was last updated by its maintainer. point in time Model Context Protocol
License AGPL-3.0 Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. as of fetch GitHub
First listed in the MCP Registry 2026-08-02 Date this server was first published to the official MCP Registry. Not a usage or quality measure. point in time Model Context Protocol
repository status active The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. as of fetch GitHub
mcp tools declared 8 tools Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. as of probe api.seiche.info
mcp endpoint status ok The server listed 8 functions when asked. as of probe api.seiche.info

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These share tags the maintainers applied themselves, such as agpl, liquidity, federal-reserve, macroeconomics. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.

This is not a recommendation and not a test result. It is a map of what the authors said their work is about.

Also from beepboop2025

How the author describes it

Topics the maintainer set on GitHub: agpl, early-warning, federal-reserve, finance, fintech, funding-markets, liquidity, macro-finance, macroeconomics, market-data, mcp, mcp-server, model-context-protocol, money-markets, open-data, open-source, repo-market, risk-monitoring, terminal.

This record as data

Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.

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Sources

  1. beepboop2025/seiche on GitHub — GitHub, observed , trust tier 3.
  2. Tools declared by the MCP server at https://api.seiche.info/mcp — api.seiche.info, observed , trust tier 1.
  3. Official MCP Registry — Model Context Protocol, observed , trust tier 1.