add_observations · MCP Memory Server

WHAT IT DOES

What add_observations does on MCP Memory Server - HTTP Streaming

AI agents use add_observations to create or update resources in MCP Memory Server - HTTP Streaming — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MCP Memory Server - HTTP Streaming environment.

WHY IT NEEDS A POLICY

Why add_observations needs a policy

This tool creates or modifies data in a reversible manner (observations can be added to entities), which is characteristic of Write operations. It does not delete data (Destructive), does not execute arbitrary code (Execute), does not move money (Financial), and does not retrieve data without side effects (Read).

From the tool's definition Tool description states it will "Add new observations to existing entities" — a reversible modification operation that creates new data entries within the knowledge graph.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

add_observations Rate-limited

add_observations stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "add_observations": {
      "limits": [
        {
          "counter": "add_observations_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches MCP Memory Server - HTTP Streaming, so you can run agents against it safely.

FAQ

Questions about add_observations

What does the add_observations tool do? +

Add new observations to existing entities in the knowledge graph. It is categorised as a Write tool in the MCP Memory Server - HTTP Streaming MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on add_observations? +

Register the MCP Memory Server - HTTP Streaming MCP server in PolicyLayer and add a rule for add_observations: 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 Memory Server - HTTP Streaming. Nothing to install.

What risk level is add_observations? +

add_observations is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit add_observations? +

Yes. Add a rate_limit block to the add_observations 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.

How do I block add_observations completely? +

Set action: deny in the PolicyLayer policy for add_observations. 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.

What MCP server provides add_observations? +

add_observations is provided by the MCP Memory Server - HTTP Streaming MCP server (songlairui/mcp-memory-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.