← Plugin catalog
Finance

Altair Research

Altair AI v1.0.0

Read Altair stock/ETF research

Create a free account to save this plugin.

From the developer

Declared capabilities

  • List research coverage
  • Compare research decisions
  • Read research reports

Declared limitations

  • Trade execution is unsupported: the plugin reads public research and has no brokerage or order tools.
  • Personal position sizing is outside the informational research workflow.
  • Report-time closes cannot answer a request for a live quote.

Not specified in the available declarations: pricing & account requirements.

Onboarding example

What does the latest Altair research say about Nvidia?
Sources & dates

Developer declarations; not independently tested. Listing last checked Nov 5, 2026. Package observed Nov 5, 2026.

View package source →

Description

From the marketplace listing

Read Altair's published AI research on about 70 US stocks and ETFs. Compare each model's rating, price target, confidence, horizon and summary, then open the underlying report to examine the bull case, bear case and risks. Intended for readers studying published market research. Coverage and analysis dates vary; report-time closes are not live quotes. The public MCP connection requires no sign-in. Reports are AI-generated for testing and information only, may contain errors, and are not financial or investment advice. The plugin does not place trades or provide personal buy or sell instructions or position sizes.

Language: English · Automatically detected from descriptions.

Changes

No changes recorded yet. Follow this plugin to keep track of future changes.

First seen Nov 5, 2026. Last seen Nov 5, 2026.

Keywords

Files & skills

File archives

Plugin package11 files · 89.3 KBBrowse files →
Skill instructions
altair-research4.36 KB

View saved version →

---
name: altair-research
description: Latest AI research on US stocks and ETFs from altairworld.com's free public MCP server. Covers about 70 tickers, including the SPY, QQQ, SOXX and XBI index ETFs (refreshed weekly) and stocks such as NVDA, AAPL, MSFT, TSLA, AVGO and META. Several Claude, GPT and Gemini models each run the same multi-agent TradingAgents pipeline (technical, sentiment, news and fundamentals analysts, bull/bear debate, trader, risk team, portfolio manager); this skill returns every model's final rating, price target, confidence, horizon and summary, and where they disagree. Use when the user asks for the outlook, rating, price target, bull or bear case, or AI research view on a stock ticker or company, the broad market, Nasdaq, semiconductors or biotech. No API key. Research for information only, not investment advice.
license: MIT
---

# Altair research

Fetches the newest published research from <https://altairworld.com/TradingAgents/> through Altair's free public MCP endpoint (`https://altairworld.com/mcp/free`): `get_research_decisions` for each model's final decision, `list_research_reports` for coverage and `read_research_report` for full reports. No key, no sign-in, no MCP setup. Every call returns current data without updating this skill.

## Run

Use Python 3.8+ (standard library only). The script is in this skill's `scripts/` folder:

```bash
python3 scripts/altair_research.py tickers                       # covered tickers and report counts
python3 scripts/altair_research.py latest                        # SPY QQQ SOXX XBI
python3 scripts/altair_research.py latest NVDA AMD               # any covered tickers
python3 scripts/altair_research.py latest TSLA --date 2026-10-14 # an earlier analysis date
python3 scripts/altair_research.py report <report-url> --section risk
```

- `tickers` lists every covered ticker with its report count, index ETFs first.
- `latest [TICKER ...]` prints one block per ticker for its newest analysis date: a table with each model's final rating, report-time close, target, target vs close, confidence and horizon, then each model's executive summary. Tickers may be space- or comma-separated, any case, with or without `$`. With no tickers it covers the four index ETFs. `--summary-chars N` sets summary length (default 600).
- `report` prints one section of a report URL from `latest`: `pm` (portfolio manager, default), `analysts` (technical, sentiment, news, fundamentals), `research` (bull/bear debate), `trader`, `risk`, or `full` (150–300 KB; avoid unless asked).
- An uncovered ticker prints "No research for …"; a `--date` without reports lists the recent analysis dates. A model whose report could not be read shows as "unavailable". Exit status 1 means the server was unreachable or every ticker failed; say so instead of guessing.

If the Altair MCP server is already connected, call its `get_research_decisions { ticker, date? }` tool for the same table data, and `read_research_report` only when the user wants a model's full reasoning (150–300 KB per report).

## Answering

1. Map company names to tickers yourself (Nvidia → NVDA, Google → GOOGL). If a ticker is not covered, say so and offer covered peers from `tickers`; never substitute another company's research silently.
2. Lead with the analysis date and the split, e.g. "NVDA, 2026-10-21: 1 Hold, 1 Overweight, 1 Underweight." Disagreement between models is the signal; don't average ratings into one verdict.
3. Give the table, then the key reasons on each side from the summaries. For "why", run `report <url> --section research` (bull/bear debate), `--section analysts` (fundamentals, news, technicals) or `--section risk` for the relevant model.
4. Say that closes are report-time, not live. Index ETFs are refreshed about weekly; other tickers less regularly, so state the date and flag research older than about 10 days (the script marks it).
5. Link the report URLs so the user can read the full reasoning.
6. End with the disclaimer: AI-generated research for testing and information only, not financial or investment advice. Never turn it into a personal buy or sell instruction or position size for the user.

Stock reports include a fundamentals analyst section built from financial statements. ETF reports are mostly technical, macro and sentiment analysis, and their fundamentals section is thin (no holdings or NAV data); say so if the user asks for fundamental valuation of an ETF.

Referenced files: 1 — file references are metadata, not package contents.

Release notes

1.0.0: Initial directory package with published stock and ETF research, model decision comparisons, full report reading, a public remote MCP connection and review scenarios.

Declared in the saved package. Remote tools may change independently.

Package details

Publisher declarations from the archived package. These are separate from our research and the live service's terms.

Package license
MIT
Package author
Altair AI
Keywords
See keywords
Review scenarios
5 positive · 3 negativeScenario counts, not test results.

Declared capabilities

  • List research coverage
  • Compare research decisions
  • Read research reports

Some manifest fields differ or could not be read. The structured report retains the source references.

Package observed Nov 5, 2026.

Technical details
First seen
Nov 5, 2026 · 00:00 UTC
Last seen
Nov 5, 2026 · 06:00 UTC
Collection status
Collected

plugin_asdk_app_6adb0256eb208191bbed83a8e1102716

Download plugin data (JSON)