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dsh-algovault

Preconfigured DeepSeek Harness bundle for the AlgoVault MCP server — composite trade calls, market regime and cross-venue funding arbitrage as mcp__algovault__* tools.

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Language
JavaScript
Created
Aug 30, 2026
Updated
Aug 30, 2026

Introduction

dsh-algovault

Mount the AlgoVault MCP server in DeepSeek Harness with one command.

This bundle ships a preconfigured @deepseek-ai/dsh-mcp-client row pointed at https://api.algovault.com/mcp. Your agent gets composite BUY / SELL / HOLD trade calls, market regime, cross-venue funding arbitrage and the live track record, as native tools.

Built by AlgoVault Labs — algovault.com

Install

dsh plugin --profile <name> add github:AlgoVaultLabs/dsh-algovault

Then restart that profile. Bundle membership is read at start, not hot-reloaded.

From the dsh.pub registry, the pinned form is:

npx dshpub add AlgoVaultLabs/dsh-algovault --ref <commit>

There is no build step and no key to configure. pnpm must be on PATH; dsh plugin forwards to it.

Tools

Every tool arrives namespaced as mcp__algovault__<tool>.

ToolReturns
get_trade_callComposite BUY / SELL / HOLD verdict for one perpetual futures asset, with confidence and regime
scan_trade_callsRanked verdicts across the top perps by open interest, in one call
get_market_regimeTRENDING_UP / TRENDING_DOWN / RANGING / VOLATILE, with a strategy hint
scan_funding_arbRanked cross-venue funding spreads for delta-neutral carry
get_track_recordAggregated PFE win rates by call type, timeframe and asset tier, plus the methodology
search_knowledgeRanked snippets on tool parameters, response shapes and integration patterns
chat_knowledgeA synthesized answer with citations over the same knowledge bundle
get_trade_signalBack-compat alias of get_trade_call. Prefer get_trade_call in new work

The bundle also ships a skill at skills/algovault-verdicts/SKILL.md that teaches the model which tool answers which question. Copy it into ~/.dsh/skills/ to load it.

Tiers

The free tier is anonymous. Install, restart, call — no key, no signup.

Paid tiers raise the quota and unlock the full funding-arb result set. Add the header in your profile's own cordis.patch.yml, not here, so an update to this bundle never overwrites your key:

- id: mcp-algovault
  name: '@deepseek-ai/dsh-mcp-client'
  config:
    serverName: algovault
    transport: streamable-http
    url: https://api.algovault.com/mcp?src=dsh-bundle
    headers:
      Authorization: !!js `Bearer ${process.env.ALGOVAULT_API_KEY}`

Set ALGOVAULT_API_KEY to your key, which looks like av_live_.... A patch replaces the whole config, so restate every field above, not only headers.

Current quotas and tiers: api.algovault.com/signup.

Model Experience

The model sees the tools above under the mcp__algovault__ prefix. Each returns a structured verdict rather than raw indicator values, so the model reads a decision and its confidence instead of assembling one.

A verdict of HOLD is a real answer, not a failure. The model should report it and stop, rather than retrying with different parameters until a directional call appears. Confidence and market regime belong in the reply beside every verdict; a BUY in a VOLATILE regime is a weaker claim than a BUY in a trending one.

AlgoVault supplies the thesis. It places no orders and holds no funds. The model should never present a verdict as an instruction to execute.

Win rates and coverage figures change. The model should quote them from a get_track_record response, never from memory.

Known Limitations

DeepSeek Harness is a developer preview and its own README warns of compatibility-breaking changes. Every published version is a release candidate. This bundle is deliberately thin for that reason: one client row, no wrappers around harness internals. Verified against @deepseek-ai/dsh@0.1.1-rc.2 and @deepseek-ai/dsh-mcp-client@0.1.1-rc.2 on 2026-08-30.

The bundled skill is not auto-discovered. The harness scans project, custom and user skill roots, and a bundle's own directory is none of those, so the copy step above is required.

MCP resources and prompts are not bridged by the harness. Tools only.

The endpoint is a hosted HTTP service. If it is unreachable at startup the harness still boots and logs an error, and the AlgoVault tools are absent for that session.

Links

License

MIT. See LICENSE.