append_run_logs

Append log entries to a specific Agent run. Use this during execution to record progress, tool calls, decisions, and errors for later replay and debugging.

SERVERTodo for AI MCP Server SOURCEtodo-for-ai/todo-for-ai-mcp

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/todo-for-ai-todo-for-ai-mcp/append-run-logs.md

WHAT IT DOES

What append_run_logs does on Todo for AI MCP Server

AI agents invoke append_run_logs to trigger actions in Todo for AI MCP Server. 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.

RISK

Why append_run_logs is rated High

append_run_logs triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs append_run_logs safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Todo for AI MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For append_run_logs, this is the rule to start with:

append_run_logs Rate-limited

append_run_logs 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "append_run_logs": {
      "limits": [
        {
          "counter": "append_run_logs_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Todo for AI MCP Server, apply this rule, and every append_run_logs call is checked against it from then on.

FAQ

Questions about append_run_logs

What does the append_run_logs tool do? +

Append log entries to a specific Agent run. Use this during execution to record progress, tool calls, decisions, and errors for later replay and debugging. It is categorised as a Execute tool in the Todo for AI MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on append_run_logs? +

Register the Todo for AI MCP Server MCP server in PolicyLayer and add a rule for append_run_logs: 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 Todo for AI MCP Server. Nothing to install.

What risk level is append_run_logs? +

append_run_logs is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit append_run_logs? +

Yes. Add a rate_limit block to the append_run_logs 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 append_run_logs completely? +

Set action: deny in the PolicyLayer policy for append_run_logs. 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 append_run_logs? +

append_run_logs is provided by the Todo for AI MCP Server MCP server (todo-for-ai/todo-for-ai-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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