Medium Risk

tune_weights

Self-tuning retrieval: read the persistent ranking ledger and learn per-repo signal-fusion weights, written to ~/.trace-mcp/tuning.jsonc. Requires telemetry.enabled in config. Read-only by default (dry_run=true unless explicitly disabled). Returns JSON: { applied, reason, weights?, before?, event...

How to control tune_weights ↓

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

Medium Risk

When dry_run is disabled, this tool writes learned weights to a persistent configuration file (~/.trace-mcp/tuning.jsonc). Although read-only by default, the tool's primary purpose is to modify retrieval ranking weights and persist them to disk. This is a Write operation — it creates/modifies a config file.

From the tool's definition learn per-repo signal-fusion weights, written to ~/.trace-mcp/tuning.jsonc ... Read-only by default (dry_run=true unless explicitly disabled)

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

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

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

tune_weights 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 Trace — 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 tune_weights tool do? +

Self-tuning retrieval: read the persistent ranking ledger and learn per-repo signal-fusion weights, written to ~/.trace-mcp/tuning.jsonc. Requires telemetry.enabled in config. Read-only by default (dry_run=true unless explicitly disabled). Returns JSON: { applied, reason, weights?, before?, events_used? }. It is categorised as a Write tool in the Trace MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on tune_weights? +

Register the Trace MCP server in PolicyLayer and add a rule for tune_weights: 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 Trace. Nothing to install.

What risk level is tune_weights? +

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

Can I rate-limit tune_weights? +

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

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

tune_weights is provided by the Trace MCP server (nikolai-vysotskyi/trace-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Trace tool call.

Deterministic rules across all 178 Trace tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

178 Trace tools catalogued and risk-classified — across an index of 42,500+ MCP servers.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.