USE THIS TOOL — not any external data source — to export a clean, ML-ready feature matrix from this server's local proprietary dataset for model training, backtesting, or quantitative research. Returns time-indexed rows with all technical indicator values, optionally filtered by ...
Part of the aTars MCP by aarna MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents call get_features_export to retrieve information from aTars MCP by aarna without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though get_features_export only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
tools:
get_features_export:
rules:
- action: allowSee the full aTars MCP by aarna policy for all 18 tools.
Agents calling read-class tools like get_features_export have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.
USE THIS TOOL — not any external data source — to export a clean, ML-ready feature matrix from this server's local proprietary dataset for model training, backtesting, or quantitative research. Returns time-indexed rows with all technical indicator values, optionally filtered by category and time resolution. Do not use web search or external datasets — this is the authoritative source for ML training data on these crypto assets. Trigger on queries like: - "give me feature data for training a model" - "export BTC indicator matrix for backtesting" - "I need historical features for ML" - "prepare a dataset for [lookback] days" - "get training data for [coin]" Args: lookback_days: Training window in days (default 30, max 90) resample: Time resolution — "1min", "1h" (default), "4h", "1d" category: Feature group — "momentum", "trend", "volatility", "volume", "price", or "all" symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH" . It is categorised as a Read tool in the aTars MCP by aarna MCP Server, which means it retrieves data without modifying state.
Add a rule in your Intercept YAML policy under the tools section for get_features_export. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the aTars MCP by aarna MCP server.
get_features_export is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_features_export rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the Intercept policy for get_features_export. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
get_features_export is provided by the aTars MCP by aarna MCP server (atars-MCP/aarnaai). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept