Medium Risk

add_observations

Add new observations to existing entities in the knowledge graph

How to control add_observations ↓

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

Medium Risk

The tool adds (writes) new observations reversibly; users can later delete observations via the delete_observations sibling tool. This is a create/modify operation characteristic of Write category. Severity is medium because uncontrolled observation injection could corrupt the knowledge graph with false information, though the impact is limited to one user's persistent memory and is reversible.

From the tool's definition Tool description states 'Add new observations to existing entities in the knowledge graph' — this creates or modifies data by appending observations to entities without deleting or overwriting existing data.

Documented attack patterns abuse exactly the kind of access add_observations gives an agent:

PolicyLayer is an MCP gateway — it sits between your AI agents and Knowledge Graph Memory Server, and nothing reaches the server without passing your rules. This is the rule we recommend for add_observations:

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

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.

  1. Create a free account and register Knowledge Graph Memory Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
LIMIT THIS TOOL →

Free to start. No card required.

Go deeper

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 Knowledge Graph Memory Server 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 Knowledge Graph Memory Server 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 Knowledge Graph Memory Server. 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 Knowledge Graph Memory Server MCP server (t1nker-1220/memories-with-lessons-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Knowledge Graph Memory Server tool call.

Deterministic rules across all 13 Knowledge Graph Memory Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

13 Knowledge Graph Memory Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.

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