Update an existing documentation file via a GitHub Pull Request for admin review. The document must already exist in the knowledge base. Content is validated locally (schema, path, sanitization, markdown lint, existence check) then a PR is automatically created. If GITHUB_TOKEN is not set, the up...
Risk signalsAccepts file system path (filePath) · Accepts raw HTML/template content (content) · Admin/system-level operation
Part of the Feathersjs server.
Free to start. No card required.
AI agents use update_documentation to create or modify resources in Feathersjs. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call update_documentation repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Feathersjs.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"update_documentation": {
"limits": [
{
"counter": "update_documentation_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Feathersjs policy for all 4 tools.
These attack patterns abuse exactly the kind of access update_documentation gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Update an existing documentation file via a GitHub Pull Request for admin review. The document must already exist in the knowledge base. Content is validated locally (schema, path, sanitization, markdown lint, existence check) then a PR is automatically created. If GITHUB_TOKEN is not set, the update is staged locally. For new documents, use submit_documentation instead.. It is categorised as a Write tool in the Feathersjs MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Feathersjs MCP server in PolicyLayer and add a rule for update_documentation: 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 Feathersjs. Nothing to install.
update_documentation 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 update_documentation 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 update_documentation. 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.
update_documentation is provided by the Feathersjs MCP server (feathersjs-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 4 Feathersjs tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.