export_ai_log_otel
[MAINTENANCE] R2-G — Run ONE bounded export pass of new ai_log_events to the configured OTel/Langfuse-compatible OTLP endpoint for a project, resuming from the durable watermark left by the previous pass. Always safe to call: returns {"status": "disabled"} immediately if MERIDIAN_AI_LOG_OTEL_ENAB...
This record as markdown: /tools/io-github-ajc3xc-meridian/export-ai-log-otel.md
What export_ai_log_otel does on Meridian
AI agents use export_ai_log_otel to create or update resources in Meridian, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Meridian environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
batch_size | integer | — | Max events to fetch this pass. Default from MERIDIAN_AI_LOG_OTEL_BATCH_SIZE (200), hard-capped at 1000. |
project_id | string | — | |
project_name | string | — | Project name — an alternative to project_id; resolved to the id internally. project_id wins if both are given. |
Parameters from the server's own tool schema.
Why export_ai_log_otel is rated Medium
An AI agent can call export_ai_log_otel faster than any human can review: one bad instruction and it creates or modifies resources in Meridian by the hundred, each call as confident as the last.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs export_ai_log_otel safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Meridian, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For export_ai_log_otel, this is the rule to start with:
export_ai_log_otel 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Meridian, apply this rule, and every export_ai_log_otel call is checked against it from then on.
Questions about export_ai_log_otel
[MAINTENANCE] R2-G — Run ONE bounded export pass of new ai_log_events to the configured OTel/Langfuse-compatible OTLP endpoint for a project, resuming from the durable watermark left by the previous pass. Always safe to call: returns {"status": "disabled"} immediately if MERIDIAN_AI_LOG_OTEL_ENABLED (or this project's own override) is off, {"status": "unavailable"} if the optional opentelemetry client library isn't installed or no endpoint is configured, {"status": "idle"} if there is nothing new to export, {"status": "sent"} on full success, {"status": "degraded"} if part of the batch sent before a chunk exhausted its bounded retries (the watermark still advanced past every chunk that DID send — no silent gaps), or {"status": "sync_failed"}/{"status": "error"} if nothing sent this pass. NEVER raises, never blocks the caller longer than a bounded overall deadline, and never mutates or deletes any ai_log_events row — Meridian's own DB stays authoritative regardless of outcome. Returns {project_id, status, sent_count, batch_size, reason}. Persistent-state disclosure: on hosted Meridian, supplied text and project/session metadata -- including task log entries, pinned decisions, sprint items, notes, handoff/goal state, and HITL queue items -- are sent to and stored in Meridian's service, in an isolated per-tenant Postgres database (Neon); self-hosted deployments keep the same categories in the configured local SQLite/Postgres database. This data is visible in the dashboard and API, and may resurface in later project context or handoffs. Notes and pinned decisions can be deleted individually; task log entries and sprint items can be deleted via the dashboard/API (not exposed as an agent-facing tool); HITL queue items and handoff state have no per-record delete. Full removal of any of this data is available via project or account deletion, using the documented controls. Do not include secrets. It is categorised as a Write tool in the Meridian MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
export_ai_log_otel accepts 3 parameters: batch_size, project_id, project_name. The full parameter table on this page comes from the server's own tool schema.
Register the Meridian MCP server in PolicyLayer and add a rule for export_ai_log_otel: 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 Meridian. Nothing to install.
export_ai_log_otel 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 export_ai_log_otel 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 export_ai_log_otel. 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.
export_ai_log_otel is provided by the Meridian MCP server (@meridianmcp/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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