Read a local file or focused region. Arrive here from localSearchCode hits or localFindFiles results. Prefer matchString or startLine/endLine over fullContent — matchString returns only the matching slices with context, keeping reads token-efficient. Chain from localSearchCode: reuse the search p...
AI agents call localGetFileContent 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 localGetFileContent. Maximum is 5 queries per call. Multiple queries run in parallel. Use the per-query `page` field to navigate through re |
Parameters from the server's own tool schema.
This tool performs read-only operations on local files, retrieving content for analysis without side effects. The emphasis on token-efficient reads and integration with search results (localSearchCode, localFindFiles) confirms it is purely a data retrieval mechanism. No write, execute, destructive, or financial operations are described.
From the tool's definition Tool description explicitly states 'Read a local file or focused region' and emphasizes retrieval options like 'matchString', 'startLine/endLine', and 'fullContent' without any modification or deletion capabilities.
Risk signalsAccepts file system path (queries[].path) · High parameter count (15 properties)
Documented attack patterns abuse exactly the kind of access localGetFileContent 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 localGetFileContent:
{
"version": "1",
"default": "deny",
"tools": {
"localGetFileContent": {}
}
} localGetFileContent is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Read a local file or focused region. Arrive here from localSearchCode hits or localFindFiles results. Prefer matchString or startLine/endLine over fullContent — matchString returns only the matching slices with context, keeping reads token-efficient. Chain from localSearchCode: reuse the search pattern as matchString to land directly on the relevant code. lineHint values from localSearchCode become startLine anchors. It is categorised as a Read tool in the Octocode MCP - AI Context Platform MCP Server, which means it retrieves data without modifying state.
localGetFileContent 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 localGetFileContent: 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.
localGetFileContent 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 localGetFileContent 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 localGetFileContent. 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.
localGetFileContent 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.