External GitHub tree inspection. Use root layout first, then drill into likely source/package dirs. Tree shape separates implementation from tests, fixtures, docs, examples, and generated code. Use githubSearchCode or githubGetFileContent for content-level work after orientation.
AI agents call githubViewRepoStructure to retrieve information from Octocode MCP - AI Context Platform without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
queries | array | Yes | Array of queries for githubViewRepoStructure. Maximum is 5 queries per call. Multiple queries run in parallel. Use the per-query `page` field to navigate throug |
Parameters from the server's own tool schema.
This tool queries GitHub repository layout/metadata and returns structural information. It has no side effects, does not execute code, does not modify data, and does not access sensitive operations. The explicit delegation to separate tools for actual content retrieval and the focus on "orientation" confirm this is a read-only inspection capability.
From the tool's definition Tool performs "External GitHub tree inspection" and advises to "Use githubSearchCode or githubGetFileContent for content-level work", indicating this tool only retrieves and displays repository structure without modifying data.
Risk signalsAccepts file system path (queries[].path) · High parameter count (12 properties) · Admin/system-level operation
Documented attack patterns abuse exactly the kind of access githubViewRepoStructure gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Octocode MCP - AI Context Platform, and nothing reaches the server without passing your rules. This is the rule we recommend for githubViewRepoStructure:
{
"version": "1",
"default": "deny",
"tools": {
"githubViewRepoStructure": {}
}
}githubViewRepoStructure is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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External GitHub tree inspection. Use root layout first, then drill into likely source/package dirs. Tree shape separates implementation from tests, fixtures, docs, examples, and generated code. Use githubSearchCode or githubGetFileContent for content-level work after orientation. It is categorised as a Read tool in the Octocode MCP - AI Context Platform MCP Server, which means it retrieves data without modifying state.
githubViewRepoStructure accepts 1 parameter: queries. Required: queries. The full parameter table on this page comes from the server's own tool schema.
Register the Octocode MCP - AI Context Platform MCP server in PolicyLayer and add a rule for githubViewRepoStructure: 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 Octocode MCP - AI Context Platform. Nothing to install.
githubViewRepoStructure is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the githubViewRepoStructure 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 githubViewRepoStructure. 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.
githubViewRepoStructure is provided by the Octocode MCP - AI Context Platform MCP server (octocode-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Octocode MCP - AI Context Platform, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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13 Octocode MCP - AI Context Platform tools catalogued and risk-classified — across an index of 43,000+ MCP servers.