Find past trades with similar market context. Use this before making a trade to learn from past experience. Returns trades with their reflections and outcomes. Uses OWM scoring when episodic memories exist, falls back to keyword matching. Args: symbol: Trading instrument to filter by (e.g. "XAUUS...
Part of the Pypi:tradememory Protocol server.
Free to start. No card required.
AI agents call recall_similar_trades to retrieve information from Pypi:tradememory Protocol 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 recall_similar_trades 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.
{
"version": "1",
"default": "deny",
"tools": {
"recall_similar_trades": {}
}
}See the full Pypi:tradememory Protocol policy for all 15 tools.
These attack patterns abuse exactly the kind of access recall_similar_trades gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Find past trades with similar market context. Use this before making a trade to learn from past experience. Returns trades with their reflections and outcomes. Uses OWM scoring when episodic memories exist, falls back to keyword matching. Args: symbol: Trading instrument to filter by (e.g. "XAUUSD") market_context: Current market conditions to match against strategy_name: Optional strategy filter limit: Max number of results (default 5). It is categorised as a Read tool in the Pypi:tradememory Protocol MCP Server, which means it retrieves data without modifying state.
Register the Pypi:tradememory Protocol MCP server in PolicyLayer and add a rule for recall_similar_trades: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Pypi:tradememory Protocol. Nothing to install.
recall_similar_trades 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 recall_similar_trades rule in your PolicyLayer 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 PolicyLayer policy for recall_similar_trades. 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.
recall_similar_trades is provided by the Pypi:tradememory Protocol MCP server (pypi:tradememory-protocol). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 15 Pypi:tradememory Protocol tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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