mcp server
AlgoVault — Crypto Quant Trade Calls
The Brain Layer for AI Trading Agents — quant calls + cross-venue arb across perp venues via MCP.
Description as published by the maintainer. Source
- version 1.26.0
- active
active — Most recent push to the repository was 2026-08-06.
What this server can do
7 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.
chat_knowledge(model, question)- Returns a synthesized natural-language answer with citations, grounded in the AlgoVault knowledge bundle (every MCP tool description, response shape, integration tutorial, and code example). Use when you need an explanation, code pattern, or how-to; for raw ranked snippets without LLM synthesis use search_knowledge (faster, no quota cost). Read-only: calls an LLM, no other side effects. Quota: Free 10/month, Starter 50, Pro 200, Enterprise 2000. Required: question.
get_market_regime(coin, exchange, timeframe)- Returns the market regime — TRENDING_UP TRENDING_DOWN RANGING VOLATILE — with confidence and a strategy hint, for one crypto perpetual futures. Composite verdict blends trend ranging and cross-venue funding rate sentiment. For a US equity use get_equity_regime. Read-only, live exchange APIs. Verified track record, on-chain verified merkle anchor. Required: coin.
get_trade_call(coin, exchange, timeframe, assetClass, includeReasoning)- Returns a composite verdict — BUY SELL HOLD trade call with confidence and market regime — for one crypto or tokenized-stock perpetual futures. One asset only; for a whole-market scan use scan_trade_calls, for US stocks use get_equity_call. Read-only: reads live exchange APIs, no orders. Verified track record, on-chain verified merkle anchor. Required: coin.
get_trade_signal(coin, exchange, timeframe, assetClass, includeReasoning)- Returns a composite verdict — BUY SELL HOLD trade call with confidence and market regime — for one crypto or tokenized-stock perpetual futures. One asset only; for a whole-market scan use scan_trade_calls, for US stocks use get_equity_call. Read-only: reads live exchange APIs, no orders. Verified track record, on-chain verified merkle anchor. [ALIAS] This tool is an alias of get_trade_call — same behavior, kept for backward compatibility. Required: coin.
scan_funding_arb(limit, minSpreadBps)- Ranked cross-venue funding arbitrage across major crypto perpetual futures venues — funding rate spreads, long one venue short another, as a BUY SELL HOLD composite verdict per pair. AI trading signal for crypto quant and Claude trading agents. Trade call via get_trade_call, market regime via get_market_regime. On-chain verified merkle anchor.
scan_trade_calls(topN, limit, rankBy, oiBasis, exchange, timeframe, includeHolds, minConfidence, oiChangeWindow, minLiquidityUsd, includeReasoning)- Returns ranked BUY SELL HOLD trade calls across the top crypto perpetual futures by open interest — one scan for whole-market coverage, each with confidence and market regime. Use this for breadth; use get_trade_call for per-coin depth and reasoning. Read-only: reads live exchange APIs, places no orders.
search_knowledge(limit, query)- Returns ranked snippets from the AlgoVault knowledge bundle answering a question about its MCP tools, response shapes, integration patterns (LangChain, LlamaIndex, MAF, CrewAI), or code examples. Call this BEFORE other tool calls to confirm parameter usage and avoid hallucinating tool shapes. Fast: BM25 lexical search, no LLM call, no quota cost. For a synthesized natural-language answer use chat_knowledge. Read-only, no side effects. Required: query.
Last successful function declaration observed on . Source: https://api.algovault.com/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://api.algovault.com/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 | 5 | 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 | 2 | 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 | 1.26.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-08-06 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | 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 | 2026-08-06 | 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 | 7 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.algovault.com | |
| mcp endpoint status | ok | The server listed 7 functions when asked. | as of probe | api.algovault.com |
Where to get it
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These share tags the maintainers applied themselves, such as crypto, funding-rate, hyperliquid, perpetual-futures. 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.
How the author describes it
Topics the maintainer set on GitHub: ai-agents, base, crypto, defi, funding-rate, hyperliquid, mcp, model-context-protocol, perpetual-futures, quant, trading, trading-signals, x402.
This record as data
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GET /api/v1/entries/mcp_server.json