Real-time market-risk intelligence for AI agents — 18 engines, crypto + US equities. Not advice.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
Manual Client & Custom JSON ConfigExpand JSON ▾
Client Config & Setup
Remote HTTPChoose your client or environment
Target File:
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Capabilities & Tool Schemas (10)
Inspect callable tools, capabilities, and parameters exposed to AI agents by Fahali.
fahali_get_market_verdictPer-symbol verdict: direction, confidence, reasoning, expected move, horizon
fahali_get_lead_timeThe verified, outcome-scored lead-time record (public)
fahali_get_forecastProbabilistic forecast over the signal's own registered horizon (6-72h), with an uncertainty cone, Brier-scored
fahali_get_flash_crash_riskFlash-crash precursor strength, or an explicit abstention
fahali_get_track_record_scorecardThe judged record with per-horizon base rates and lift
fahali_get_contagion_mapCross-asset tail-dependence and correlated clusters
Documentation Overview
Fahali — Financial Risk MCP Server for AI Agents
Give your agent a risk conscience. Fahali gives AI agents a callable financial-risk layer: portfolio risk, stress losses, crypto risk, contagion, crash precursors and market verdicts. Read-only — your agent already fetches prices; Fahali tells it what those prices mean for capital at risk. It returns a judged read with its confidence, the inputs it is missing, and a signed receipt, so your agent can check its own conviction against something scored against outcomes instead of raw prices it has to interpret blindly.
Observation, not advice. Fahali watches and explains market risk. It never tells you or your agent what to buy or sell. Read-only: no order routing, no path to capital.
Why an agent cites Fahali instead of a price feed
- Verified lead time. Per engine, the median hours ahead of the move on its correct material warnings, scored against what happened, with the misses in the same record. Your agent can weight a signal by proven lead, not by tone. Public, no key:
GET /api/track-record/lead-time. - Signed receipts. Every verdict carries a SHA-256 receipt and a provenance root. When your agent quotes Fahali, it can attach proof of what was said and when.
- A judged record with public replays. Predictive signals are graded against a disclosed, versioned method at their own horizon, and wrong calls stay on the record. Analytical engines are labelled observation-only rather than scored as forecasts, because grading an observation against a price move would manufacture a hit rate that means nothing. Methodology: fahaliai.com/methodology.
- Honest absence. Missing data says so. Quiet markets resolve as unresolved, never as wins. Some tools abstain by design: whale tracking returns an explicit "no on-chain data source" rather than inventing positions.
Coverage is crypto 24/7 and US equities and ETFs during market hours. Live coverage and engine counts are reported at GET /api/public/stats rather than asserted here, because the active set changes.
See it before you sign up
The lead-time record is public. This is the fastest way to confirm Fahali is scored against outcomes:
Connect
Remote MCP (recommended, nothing to install):
Auth: OAuth 2.1 ("Connect with Fahali") or a static key, Authorization: Bearer sk_live_.... Grab a free developer key (50 calls/day, no card) at app.fahaliai.com/developer. In Claude, ChatGPT, or Cursor, add the URL above as a connector. Listed in the official MCP registry as com.fahaliai/fahali.
Run this repo as a local stdio proxy:
It forwards each tool call to the upstream Fahali API; tier is enforced upstream.
Example: a pre-trade risk check
examples/pre-trade-check is a runnable agent (zero dependencies, one command) that asks Fahali, before a position is opened: is a flash-crash precursor firing, what is the judged read and what data is missing, and how early does the record say this engine usually warns. It then prints a PROCEED / CAUTION / HOLD posture and the receipt.
Tools
Around 30 tools. Most are read-only market intelligence; a few agent-workspace tools (memory, custom alerts) write only to your own workspace, never to markets. Highlights:
| Tool | Returns |
|---|---|
fahali_get_market_verdict | Per-symbol verdict: direction, confidence, reasoning, expected move, horizon |
fahali_get_lead_time | The verified, outcome-scored lead-time record (public) |
fahali_get_forecast | Probabilistic forecast over the signal's own registered horizon (6-72h), with an uncertainty cone, Brier-scored |
fahali_get_flash_crash_risk | Flash-crash precursor strength, or an explicit abstention |
fahali_get_track_record_scorecard | The judged record with per-horizon base rates and lift |
fahali_get_contagion_map | Cross-asset tail-dependence and correlated clusters |
fahali_get_microstructure_proxy | Absorption inferred from public microstructure only - we do not see off-exchange prints |
fahali_get_capital_flow | Order-flow imbalance proxy (no fabricated institutional/retail split) |
fahali_get_market_regime | Current regime read |
fahali_run_shock_test | Stress-test a portfolio against a scenario |
Full tool schemas: mcp.fahaliai.com.
Pricing
Free developer key (50 calls/day) for exploration. Agent lanes from $49/mo (10k calls), $199 (100k), $999 (1M). Human app tiers from $19/mo at fahaliai.com.
Links
- App: app.fahaliai.com
- MCP docs / health: mcp.fahaliai.com
- Methodology (how signals are graded): fahaliai.com/methodology
- Developer / API: fahaliai.com/developer
- Privacy: app.fahaliai.com/privacy
Built by Future Legends Inc. Observation, not advice.
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Adoption & maintenance
Factual signals from GitHub, npm, and our automated checks — not a rating.
Last commit
1mo ago
Most recent push to the default branch.
Tools exposed
10
Callable tools this server registers over MCP.
Directory activity
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Frequently Asked Questions about Fahali
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CategoryFinance & Fintech
11/15 checks healthy over the last 46d
49Quality signal: Fair · 49/100How this signal is calculated ▾
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Verified ownership10/20
Documentation & tools25/30
Adoption & activity2/15
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