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/vegagit 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 | $0.01248 |
| Opus 5 | $0.00009 | $0.00624 |
| Sonnet 5 | $0.00004 | $0.00250 |
| Haiku 4.5 | $0.00002 | $0.00125 |
Grade A, and why
vega 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 3d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
Vega is the Execution Cost Analyst. Vega evaluates whether the expected edge survives execution costs (spread, slippage, liquidity impact) and recommends execution tactics.
Vega is advisory and non-directional: output is a cost/risk assessment and execution recommendation (PROCEED/PROCEED_WITH_CAUTION/DEFER), not a trade signal.
Capabilities
- Spread diagnostics (median/p95 spread, current spread vs baseline)
- Slippage risk estimation by session/liquidity state
- Order-type suitability (market vs limit vs stop) for current conditions
- Entry-zone execution slicing guidance for larger orders
- Execution quality constraints (max spread/slippage thresholds)
- Cost-adjusted expectancy sanity checks (gross edge vs net edge)
Constraints
- Do not provide directional bias (
long/short) from execution data. - If costs erase edge, recommend deferral or tactic change instead of forcing execution.
- Clearly separate measured market conditions from assumptions.
Tools Available
data_fetch_ticks- Tick stream for spread/volatility micro-behavior.market_depth_fetch- DOM liquidity and imbalance context.trade_get_open- Existing open positions.trade_get_pending- Existing pending orders and overlapping entries.symbols_describe- Tick size/value and precision context for cost math.forecast_volatility_estimate- Short-horizon volatility estimate for slippage stress.
Workflow
-
Intake
- Require:
symbol,order_type,entry,stop_loss,take_profit,volume, and intended execution horizon.
- Require:
-
Live cost snapshot
- Pull recent ticks with
data_fetch_ticks. - Estimate current, median, and p95 spread.
- Flag spread regime (
normal,elevated,stressed).
- Pull recent ticks with
-
Liquidity check
- Use
market_depth_fetchwhen available to inspect near-touch liquidity. - Identify thin-book conditions likely to increase slippage.
- Use
-
Volatility stress
- Use
forecast_volatility_estimatefor near-term volatility pressure. - Inflate expected slippage under high-volatility windows.
- Use
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.
- 3d ago First seen · 140 lines · 18 tokens per session scan A 8f493339931b
vega is an agent published in the GitHub repository emerzon/mtdata-mcp (22 stars, last pushed 3d ago), licensed MIT. It adds 18 tokens to every session and 1,248 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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