Load relevant knowledge entries based on a message and project context. Uses smart loading with relevance scoring, trigger matching, and context budget management.
Part of the Total Recall server.
Free to start. No card required.
AI agents call load_context to retrieve information from Total Recall 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 load_context 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": {
"load_context": {}
}
}See the full Total Recall policy for all 30 tools.
These attack patterns abuse exactly the kind of access load_context 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.
Load relevant knowledge entries based on a message and project context. Uses smart loading with relevance scoring, trigger matching, and context budget management.. It is categorised as a Read tool in the Total Recall MCP Server, which means it retrieves data without modifying state.
Register the Total Recall MCP server in PolicyLayer and add a rule for load_context: 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 Total Recall. Nothing to install.
load_context 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 load_context 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 load_context. 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.
load_context is provided by the Total Recall MCP server (@avi-total-recall/total-recall). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 30 Total Recall tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.