Market Intelligence MCP Server

@bullrundata/market-intelligence npm v0.5.0

Published by @bullrundata — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.

Market Intelligence MCP Server — recession probability, sector rotation, institutional positioning, macro cascade scenario analysis, real estate calculators, and economic data. Powered by the BullrunData API.

Trust grade
A
96/100
Last scanned get badge →
Trust
A · 96/100
Adoption risk for you: the threat score, then adjusted down for blast radius, publisher verification and how much the scan could see. Deterministic; every point is auditable.
Capability
Moderate
Blast radius if it went rogue — what the server’s tools could reach. Independent of trust.
Coverage
Source
How much the scan could actually inspect. Shallow coverage is stated, never hidden.
Share this Trust Score
𝕏 Share LinkedIn Reddit
A Why this grade threat 100 − adoption risk = 96/100

The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.

1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:

The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.

2. Client adoption risk — 100 − 4 = 96. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:

PointsAdoption-risk factor
−3 capability blast radius (moderate) — client exposure if the model is manipulated
−1 publisher verification (public source) — no provenance, but the source is public and inspectable

Capability observations and info notes are shown under Findings but never scored. Open any row's finding below for the file, line and evidence behind a deduction.

Findings 1

medium Hardcoded egress to an external endpoint (dist/auth/oauth-provider.js)MTC-SRC-003

In the server's implementation (`dist/auth/oauth-provider.js:108`): A hardcoded outbound call to a fixed external host inside server code is a classic exfiltration/telemetry channel — especially paired with reads of local data. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.

Evidence: const tokenRes = await fetch('https://github.com/login/oauth/access_token', { method: 'POST', headers:

Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.

Location: server dist/auth/oauth-provider.js

Tools 27

Each tool and what it can reach — statically extracted from the published source.

  • brrrr_analysisno sensitive capability
  • cascade_analysisno sensitive capability
  • cascade_by_categoryno sensitive capability
  • cascade_listno sensitive capability
  • cascade_searchno sensitive capability
  • cftc_contracts_listno sensitive capability
  • cftc_positioning_detailno sensitive capability
  • confirmation_statusno sensitive capability
  • dashboard_summaryno sensitive capability
  • economic_indicatorno sensitive capability
Show 17 more tools ↓
  • employment_datano sensitive capability
  • fed_stanceno sensitive capability
  • housing_cycleno sensitive capability
  • housing_datano sensitive capability
  • inflation_datano sensitive capability
  • institutional_cftcno sensitive capability
  • institutional_ticno sensitive capability
  • interest_ratesno sensitive capability
  • investment_property_analysisno sensitive capability
  • list_indicatorsno sensitive capability
  • market_regimeno sensitive capability
  • market_sentimentno sensitive capability
  • recession_indicatorsno sensitive capability
  • recession_probabilityno sensitive capability
  • sectors_flowsno sensitive capability
  • sectors_rotationno sensitive capability
  • yield_curveno sensitive capability

What this scan could not see

Versions 2

Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.

VersionScoreFindingsEngineScanned
v0.5.0 latest A 96/100 1 1.13.0 2026-09-09
v0.3.1 A 96/100 1 1.12.1 2026-08-03

Embed this score

Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.

MCP Trust Score: A · 96/100
Markdown (GitHub README)
[![MCP Trust Score](https://mcptrustchecker.com/registry/bullrundata-market-intelligence/badge.svg)](https://mcptrustchecker.com/registry/bullrundata-market-intelligence)
HTML
<a href="https://mcptrustchecker.com/registry/bullrundata-market-intelligence"><img src="https://mcptrustchecker.com/registry/bullrundata-market-intelligence/badge.svg" alt="MCP Trust Score" height="20"></a>
Prefer shields.io styling? Point it at https://mcptrustchecker.com/registry/bullrundata-market-intelligence/badge.json via https://img.shields.io/endpoint?url=…

Verify this score yourself

The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.

npx mcptrustchecker scan @bullrundata/market-intelligence --online

Use the free API → How scoring works

More in Developer Tools