Save a new memory rule/fact about the project. Use this whenever the user states a preference, decision, constraint, or piece of context that should persist across sessions.
AI agents use add_memory to create or update resources in mcp-Agentmemory — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your mcp-Agentmemory environment.
This tool writes/creates new memory entries persistently but does not delete, execute arbitrary code, move financial assets, or irreversibly modify existing data. The operation is reversible (memories can be deleted via the sibling delete_memory tool). Severity is low because misuse would only result in storing incorrect or irrelevant project context, with no cascading system effects or data loss.
From the tool's definition Tool description states 'Save a new memory rule/fact about the project', which creates new data entries in the memory system. No deletion, overwrite, or destructive operation is indicated.
Attacks that exploit this kind of access
Save a new memory rule/fact about the project. Use this whenever the user states a preference, decision, constraint, or piece of context that should persist across sessions. It is categorised as a Write tool in the mcp-Agentmemory MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the mcp-Agentmemory MCP server in PolicyLayer and add a rule for add_memory: 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 mcp-Agentmemory. Nothing to install.
add_memory is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the add_memory 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 add_memory. 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.
add_memory is provided by the mcp-Agentmemory MCP server (obidel/agentmemory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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