backfill_semantic_embeddings
Generuje embeddingi dla wspomnień które jeszcze ich nie mają.
This record as markdown: /tools/mapi-agent-memory/backfill-semantic-embeddings.md
What backfill_semantic_embeddings does on Mapi Agent Memory
AI agents invoke backfill_semantic_embeddings to trigger actions in Mapi Agent Memory. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why backfill_semantic_embeddings is rated High
This tool executes a background computation (semantic embedding generation) over existing memory records. It is not a simple read (it modifies records by adding embeddings), not purely destructive, but it runs a batch processing operation. Write could apply since it updates records, but the generative/execution nature of the operation (running ML embedding models over data) makes Execute more appropriate.
From the tool's definition 'Generuje embeddingi' (Generates embeddings) for memories that don't yet have them — triggers a computational/generative operation over stored data
Attacks that exploit this kind of access
The rule that runs backfill_semantic_embeddings safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mapi Agent Memory, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For backfill_semantic_embeddings, this is the rule to start with:
backfill_semantic_embeddings stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mapi Agent Memory, apply this rule, and every backfill_semantic_embeddings call is checked against it from then on.
Questions about backfill_semantic_embeddings
Generuje embeddingi dla wspomnień które jeszcze ich nie mają. It is categorised as a Execute tool in the Mapi Agent Memory MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mapi Agent Memory MCP server in PolicyLayer and add a rule for backfill_semantic_embeddings: 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 Mapi Agent Memory. Nothing to install.
backfill_semantic_embeddings is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the backfill_semantic_embeddings 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 backfill_semantic_embeddings. 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.
backfill_semantic_embeddings is provided by the Mapi Agent Memory MCP server (cabo0m/mapi-agent-memory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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