<tool> <purpose>Check if codebases are indexed and get their status information</purpose> <enhanced_features> <feature>Shows completion statistics for finished indexing (success rates, processing time, performance metrics)</feature> <feature>Displays batch processing details (successful/skipped b...
AI agents call get_indexing_status to retrieve information from DeepContext without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only retrieves indexing status information and statistics. It performs no modifications, deletions, code execution, or financial transactions. The purpose is purely informational — checking state and displaying metrics. This is a classic Read operation with minimal risk.
From the tool's definition Tool name 'get_indexing_status' and description 'Check if codebases are indexed and get their status information' and 'Shows completion statistics for finished indexing', 'Displays batch processing details', 'References log files' — all indicate querying and…
Documented attack patterns abuse exactly the kind of access get_indexing_status gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and DeepContext, and nothing reaches the server without passing your rules. This is the rule we recommend for get_indexing_status:
{
"version": "1",
"default": "deny",
"tools": {
"get_indexing_status": {}
}
}get_indexing_status is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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<tool> <purpose>Check if codebases are indexed and get their status information</purpose> <enhanced_features> <feature>Shows completion statistics for finished indexing (success rates, processing time, performance metrics)</feature> <feature>Displays batch processing details (successful/skipped batches)</feature> <feature>References log files for detailed debugging</feature> </enhanced_features> <when_to_use> <scenario>Before indexing to check if already done</scenario> <scenario>After indexing to see completion statistics and success rates</scenario> <scenario>Debug why search returned no results</scenario> <scenario>Confirm indexing completed successfully</scenario> <scenario>Get overview of all indexed codebases</scenario> </when_to_use> <parameters> <parameter name=. It is categorised as a Read tool in the DeepContext MCP Server, which means it retrieves data without modifying state.
Register the DeepContext MCP server in PolicyLayer and add a rule for get_indexing_status: 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 DeepContext. Nothing to install.
get_indexing_status 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 get_indexing_status 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 get_indexing_status. 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.
get_indexing_status is provided by the DeepContext MCP server (wildcard-official/deepcontext-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 4 DeepContext tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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4 DeepContext tools catalogued and risk-classified — across an index of 42,500+ MCP servers.