set_executor_config
[MAINTENANCE] Store per-project executor defaults (repo_path, env_file, test_cmd, test_min, deploy_cmd, shell_type, branch). Merges onto the existing config — other keys (hostnames, filesystem_roots, …) are preserved. Pass repo_paths as an array of {cwd, hostname} known locations; they are merged...
This record as markdown: /tools/io-github-ajc3xc-meridian/set-executor-config.md
What set_executor_config does on Meridian
AI agents use set_executor_config 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 |
|---|---|---|---|
branch | string | — | |
env_file | string | — | |
test_cmd | string | — | |
test_min | integer | — | |
max_turns | integer | — | Turn ceiling injected into the /goal string ('Stop after N turns'). Default 200. |
repo_path | string | — | |
deploy_cmd | string | — | |
project_id | string | — | |
repo_paths | array | — | Known locations [{cwd, hostname}] — merged into existing repo_paths, not overwritten. |
shell_type | string | — | |
project_name | string | — | Project name — an alternative to project_id; resolved to the id internally. project_id wins if both are given. |
filesystem_roots | array | — | Directories the tunnel's filesystem connector may serve (unioned across the tenant's projects). Overwrites the existing list. |
Parameters from the server's own tool schema.
Why set_executor_config is rated Medium
An AI agent can call set_executor_config 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 signalsAccepts file system path (repo_paths[].cwd) · Accepts URL/endpoint input (repo_paths[].hostname) · High parameter count (18 properties)
Attacks that exploit this kind of access
The rule that runs set_executor_config 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 set_executor_config, this is the rule to start with:
set_executor_config 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 set_executor_config call is checked against it from then on.
Questions about set_executor_config
[MAINTENANCE] Store per-project executor defaults (repo_path, env_file, test_cmd, test_min, deploy_cmd, shell_type, branch). Merges onto the existing config — other keys (hostnames, filesystem_roots, …) are preserved. Pass repo_paths as an array of {cwd, hostname} known locations; they are merged into the existing repo_paths (deduped) rather than overwriting, so manual + hook-registered entries coexist. Executor sessions auto-load these when start_session(role='executor') is used. Credentials rule is always injected separately: read secrets from env_file only, never remote shell. 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.
set_executor_config accepts 12 parameters: branch, env_file, test_cmd, test_min, max_turns, repo_path, deploy_cmd, project_id, repo_paths, shell_type, project_name, filesystem_roots. 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 set_executor_config: 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.
set_executor_config 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 set_executor_config 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 set_executor_config. 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.
set_executor_config 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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