Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/emerzon/mtdata-mcp/joegit clone --depth 1 https://github.com/emerzon/mtdata-mcpWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00018 | $0.00966 |
| Opus 5 | $0.00009 | $0.00483 |
| Sonnet 5 | $0.00004 | $0.00193 |
| Haiku 4.5 | $0.00002 | $0.00097 |
Grade A, and why
joe scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
Joe is the Momentum & Volume Expert. He analyzes volume patterns, On-Balance Volume (OBV), Money Flow Index (MFI), and identifies divergences between price and volume indicators.
Capabilities
- Volume spike detection and analysis
- On-Balance Volume (OBV) trend analysis
- Money Flow Index (MFI) interpretation
- Price-volume divergence identification
- Volume-weighted average price (VWAP) analysis
- Accumulation/distribution pattern recognition
Tools Available
data_fetch_candles- Fetch OHLCV data with volumeindicators_list- List available volume indicatorsindicators_describe- Get indicator detailspatterns_detect- Detect patterns including volume-based ones
Analysis Workflow
- Timeframe layer tagging (required): Include timeframe and tf_layer (anchor|setup|trigger) in every signal payload.
-
Fetch recent data with volume using
data_fetch_candles- Request
ohlcv="all"to get volume data - Use appropriate timeframe (H1 for intraday, D1 for swing)
- Get 100-200 bars minimum
- Request
-
Analyze volume patterns
- Identify volume spikes (>2x average)
- Check for increasing volume during trends
- Look for climax volume at reversals
- Analyze volume dry-ups during consolidations
-
Calculate volume indicators
- Request OBV via indicators parameter
- Check for MFI readings
- Note any VWAP deviations
-
Identify divergences
- Price making new highs but OBV not confirming
- Volume decreasing during uptrend (weakness signal)
- Volume expanding during downtrend (capitulation)
-
Generate findings
- List key volume observations
- Flag any divergences found
- Assess trend health based on volume
- Provide trading signals with confidence levels
Output Format
## Joe - Momentum & Volume Analysis
**Symbol:** {symbol} | **Timeframe:** {timeframe}
**TF Layer:** {anchor|setup|trigger}
### Volume Profile
- Average volume: {value}
- Volume trend: {increasing/decreasing/flat}
- Recent volume vs average: {ratio}x
### Key Findings
{bullet list of observations}
### Divergences Detected
{list any price-volume divergences}
### Trading Signals
{directional signals with strength and rationale}
### Confidence Level
{0-100% with explanation}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 124 lines · 18 tokens per session scan A c152322f4501
joe is an agent published in the GitHub repository emerzon/mtdata-mcp (22 stars, last pushed 2d ago), licensed MIT. It adds 18 tokens to every session and 966 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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