Search code by keyword/topic → returns ranked source code snippets within a token budget. Use when you need to READ actual code for a concept or feature. For structured task context with tests and entry points, use get_task_context instead. For symbol metadata without source, use search. Read-onl...
AI agents call get_feature_context to retrieve information from Trace without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a read-only search and retrieval operation. It searches code by keywords and returns ranked source code snippets along with metadata (symbol_id, name, file, source, score). No data is created, modified, deleted, or executed. The explicit 'Read-only' statement and JSON/Markdown return format confirm this is a pure query operation with no side effects.
From the tool's definition Tool description explicitly states 'Search code by keyword/topic → returns ranked source code snippets' and 'Read-only.' The function returns code snippets and metadata without modification capabilities.
Documented attack patterns abuse exactly the kind of access get_feature_context gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Trace, and nothing reaches the server without passing your rules. This is the rule we recommend for get_feature_context:
{
"version": "1",
"default": "deny",
"tools": {
"get_feature_context": {}
}
}get_feature_context is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Search code by keyword/topic → returns ranked source code snippets within a token budget. Use when you need to READ actual code for a concept or feature. For structured task context with tests and entry points, use get_task_context instead. For symbol metadata without source, use search. Read-only. Returns JSON (default) or Markdown: { items: [{ symbol_id, name, file, source, score }], token_usage } | { content:. It is categorised as a Read tool in the Trace MCP Server, which means it retrieves data without modifying state.
Register the Trace MCP server in PolicyLayer and add a rule for get_feature_context: 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 Trace. Nothing to install.
get_feature_context 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_feature_context 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_feature_context. 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_feature_context is provided by the Trace MCP server (nikolai-vysotskyi/trace-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 178 Trace tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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178 Trace tools catalogued and risk-classified — across an index of 42,500+ MCP servers.